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### Start CORE Services with Docker Compose (Bash)

Source: https://docs.heysol.ai/self-hosting/docker

This command starts the CORE services in detached mode using Docker Compose. Ensure you have Docker and Docker Compose installed and have configured your environment variables in the .env file. This command is essential for launching a self-hosted CORE instance.

```bash
docker compose up -d
```

--------------------------------

### Clone CORE Repository and Navigate to Docker Directory (Bash)

Source: https://docs.heysol.ai/self-hosting/docker

This snippet demonstrates how to clone the CORE repository from GitHub and then navigate into the Docker hosting directory. It assumes you have Git installed. This is a prerequisite for the manual Docker deployment.

```bash
# Clone the repository
git clone https://github.com/RedPlanetHQ/core.git
cd core/hosting/docker
```

--------------------------------

### Configure Session Startup and Memory Organization in claude.md

Source: https://docs.heysol.ai/concepts/spaces

This markdown snippet illustrates how to configure session startup behavior and memory organization within a 'claude.md' file. It specifies checking a particular space for context at the start of each session and directing specific conversation types to designated spaces.

```markdown
## Session Startup
- At the start of every session, check the Core-Features space for relevant context

## Memory Organization
- Store all feature discussions in Core-Features space
- Store marketing conversations in Reddit-Marketing space
```

--------------------------------

### Configure Memory Ingestion Rules

Source: https://docs.heysol.ai/integrations/overview

Example rules to control which activities are ingested into your CORE memory graph. These rules allow for granular filtering based on assignment, channel, or repository.

```text
Only add Linear issues that are assigned to me
Ignore Slack messages from #random channel
Add all GitHub commits to the TaskMaster repository
```

--------------------------------

### Install CORE MCP Server for Claude Code CLI

Source: https://docs.heysol.ai/providers/claude-code

This command registers the CORE MCP server with Claude Code, establishing an HTTP connection endpoint for memory operations. Ensure you have Claude Code installed and a CORE account.

```bash
claude mcp add --transport http core-memory https://core.heysol.ai/api/v1/mcp?source=Claude-Code
```

--------------------------------

### Configure CORE MCP in Windsurf (OAuth)

Source: https://docs.heysol.ai/providers/windsurf

This JSON configuration snippet is used within Windsurf IDE's settings to connect to CORE's memory system via OAuth authentication. Ensure Windsurf IDE is installed and you have a CORE account. This configuration enables the 'core-memory' MCP server.

```json
{
  "mcpServers": {
    "core-memory": {
      "serverUrl": "https://core.heysol.ai/api/v1/mcp?source=windsurf"
    }
  }
}
```

--------------------------------

### List Spaces API Endpoint

Source: https://docs.heysol.ai/concepts/spaces

The API endpoint for retrieving a list of all available spaces. This is a GET request.

```http
GET /api/v1/spaces
```

--------------------------------

### OpenAPI Specification for Listing and Searching Spaces

Source: https://docs.heysol.ai/api-reference/listsearch-spaces

This OpenAPI 3.0 specification defines the `/api/v1/spaces` endpoint for retrieving a list of spaces. It includes details on supported HTTP methods (GET), authentication (Bearer Token), query parameters for searching (`q`), and the structure of the successful response (200 OK) which returns an array of Space objects. The specification also defines the `Space` schema.

```yaml
openapi: 3.0.0
info:
  title: Spaces API
  version: v1
servers:
  - url: '{protocol}://{domain}'
    description: Configurable CORE server
    variables:
      protocol:
        type: enum<string>
        enum:
          - http
          - https
        description: The protocol to use
        default: https
      domain:
        type: string
        description: The CORE API domain
        default: core.heysol.ai
paths:
  /api/v1/spaces:
    get:
      summary: Get list of spaces with optional search filtering
      operationId: listSpaces
      security:
        - bearerAuth:
            - "read:spaces"
      parameters:
        - name: q
          in: query
          description: Search query for space names
          required: false
          schema:
            type: string
      responses:
        '200':
          description: List of spaces
          content:
            application/json:
              schema:
                type: array
                items:
                  $ref: '#/components/schemas/Space'
              examples:
                example:
                  value:
                    - id: "<string>"
                      name: "<string>"
                      description: "<string>"
                      createdAt: "2023-11-07T05:31:56Z"
                      updatedAt: "2023-11-07T05:31:56Z"
                      userId: "<string>"
        '401':
          description: Unauthorized
      deprecated: false
components:
  schemas:
    Space:
      type: object
      properties:
        id:
          type: string
        name:
          type: string
        description:
          type: string
        createdAt:
          type: string
          format: date-time
        updatedAt:
          type: string
          format: date-time
        userId:
          type: string
  securitySchemes:
    bearerAuth:
      type: http
      scheme: bearer
      description: |
        Bearer token authentication supports:
        - Personal API tokens (PATs)
        - OAuth2 access tokens
        - JWT tokens

        Example: `Authorization: Bearer your_token_here`
```

--------------------------------

### Configure Core Memory MCP Project Rule in Cursor

Source: https://docs.heysol.ai/providers/cursor

This snippet provides the configuration for a Cursor project rule that enables the Core Memory MCP. It includes a description, an `alwaysApply` flag, and a detailed set of instructions for the AI assistant to follow during its startup sequence, prioritizing memory search.

```text
theme={null}
---
description: Core Memory MCP Instructions
alwaysApply: true
---

⚠️ **CRITICAL: READ THIS FIRST - MANDATORY MEMORY PROTOCOL** ⚠️

You are an AI coding assistant with access to CORE Memory - a persistent knowledge system that maintains project context, learnings, and continuity across all coding sessions.

## 🔴 MANDATORY STARTUP SEQUENCE - DO NOT SKIP 🔴

**BEFORE RESPONDING TO ANY USER MESSAGE, YOU MUST EXECUTE THESE TOOLS IN ORDER:**

### STEP 1 (REQUIRED): Search for Relevant Context

EXECUTE THIS TOOL FIRST:
`memory_search`
- Previous discussions about the current topic
- Related project decisions and implementations
- User preferences and work patterns
- Similar problems and their solutions

**Additional search triggers:**
- User mentions "previously", "before", "last time", or "we discussed"
- User references past work or project history
- Working on the CORE project (this repository)
- User asks about preferences, patterns, or past decisions
- Starting work on any feature or bug that might have history

**How to search effectively:**
- Write complete semantic queries, NOT keyword fragments
- Good: `"Manoj's preferences for API design and error handling"`
- Bad: `"manoj api preferences"`
- Ask: "What context am I missing that would help?"
- Consider: "What has the user told me before that I should remember?"

```

--------------------------------

### Get Space Details API Endpoint

Source: https://docs.heysol.ai/concepts/spaces

The API endpoint for fetching detailed information about a specific space, identified by its '{spaceId}'. This is a GET request.

```http
GET /api/v1/spaces/{spaceId}
```

--------------------------------

### Get Space Episodes API Endpoint

Source: https://docs.heysol.ai/concepts/spaces

The API endpoint for retrieving all episodes associated with a specific space, identified by its '{spaceId}'. This is a GET request.

```http
GET /api/v1/spaces/{spaceId}/episodes
```

--------------------------------

### AGENTS.md Configuration for CORE Memory Protocol

Source: https://docs.heysol.ai/providers/windsurf

This markdown configuration defines the AI assistant's behavior when interacting with CORE Memory. It mandates the execution of the 'memory_search' tool before responding to any user message to retrieve relevant context, project history, and user preferences. It also provides guidelines for writing effective search queries.

```markdown
---
trigger: always_on
---

⚠️ **CRITICAL: READ THIS FIRST - MANDATORY MEMORY PROTOCOL** ⚠️

You are an AI coding assistant with access to CORE Memory - a persistent knowledge system that maintains project context, learnings, and continuity across all coding sessions.

## 🔴 MANDATORY STARTUP SEQUENCE - DO NOT SKIP 🔴

**BEFORE RESPONDING TO ANY USER MESSAGE, YOU MUST EXECUTE THESE TOOLS IN ORDER:**

### STEP 1 (REQUIRED): Search for Relevant Context

EXECUTE THIS TOOL FIRST:
`memory_search`

- Previous discussions about the current topic
- Related project decisions and implementations
- User preferences and work patterns
- Similar problems and their solutions

**Additional search triggers:**

- User mentions "previously", "before", "last time", or "we discussed"
- User references past work or project history
- Working on the CORE project (this repository)
- User asks about preferences, patterns, or past decisions
- Starting work on any feature or bug that might have history

**How to search effectively:**

- Write complete semantic queries, NOT keyword fragments
- Good: `"Manoj's preferences for API design and error handling"`
- Bad: `"manoj api preferences"`
- Ask: "What context am I missing that would help?"
- Consider: "What has the user told me before that I should remember?"

```

--------------------------------

### Get Space Summary API Endpoint

Source: https://docs.heysol.ai/concepts/spaces

The API endpoint for retrieving the automatically generated summary of a specific space, identified by its '{spaceId}'. This is a GET request.

```http
GET /api/v1/spaces/{spaceId}/summary
```

--------------------------------

### OpenAPI Specification for Get Episode Facts

Source: https://docs.heysol.ai/api-reference/get-episode-facts

This OpenAPI specification defines the GET /api/v1/episodes/{episodeId}/facts API endpoint. It outlines the request parameters, authentication methods (Bearer token), and the structure of the JSON response containing episode facts, including content, type, confidence, and validity periods. Note: This is a specification, not executable code.

```yaml
openapi.json get /api/v1/episodes/{episodeId}/facts
paths:
  path: /api/v1/episodes/{episodeId}/facts
  method: get
  servers:
    - url: '{protocol}://{domain}'
      description: Configurable CORE server
      variables:
        protocol:
          type: enum<string>
          enum:
            - http
            - https
          description: The protocol to use
          default: https
        domain:
          type: string
          description: The CORE API domain
          default: core.heysol.ai
  request:
    security:
      - title: bearerAuth
        parameters:
          query: {}
          header:
            Authorization:
              type: http
              scheme: bearer
              description: |
                Bearer token authentication supports:
                - Personal API tokens (PATs)
                - OAuth2 access tokens
                - JWT tokens

                Example: `Authorization: Bearer your_token_here`
          cookie: {}
    parameters:
      path:
        episodeId:
          schema:
            - type: string
              required: true
      query: {}
      header: {}
      cookie: {}
    body: {}
  response:
    '200':
      application/json:
        schemaArray:
          - type: array
            items:
              allOf:
                - type: object
                  properties:
                    id:
                      type: string
                    content:
                      type: string
                    type:
                      type: string
                    confidence:
                      type: number
                    validFrom:
                      type: string
                      format: date-time
                    validTo:
                      type: string
                      format: date-time
        examples:
          example:
            value:
              - id: <string>
                content: <string>
                type: <string>
                confidence: 123
                validFrom: '2023-11-07T05:31:56Z'
                validTo: '2023-11-07T05:31:56Z'
        description: Episode facts
  deprecated: false
  type: path
components:
  schemas: {}
```

--------------------------------

### GET /api/v1/episodes/{episodeId}/facts

Source: https://docs.heysol.ai/api-reference/get-episode-facts

Retrieves a list of facts or statements associated with a given episode ID. This endpoint supports Bearer token authentication.

```APIDOC
## GET /api/v1/episodes/{episodeId}/facts

### Description
Retrieves a list of facts or statements associated with a given episode ID. This endpoint supports Bearer token authentication.

### Method
GET

### Endpoint
/api/v1/episodes/{episodeId}/facts

### Parameters
#### Path Parameters
- **episodeId** (string) - Required - The ID of the episode for which to retrieve facts.

#### Query Parameters
None

#### Request Body
None

### Request Example
None

### Response
#### Success Response (200)
- **id** (string) - The unique identifier for the fact.
- **content** (string) - The factual statement.
- **type** (string) - The type of fact.
- **confidence** (number) - The confidence score for the fact.
- **validFrom** (string) - The date and time from which the fact is valid (ISO 8601 format).
- **validTo** (string) - The date and time until which the fact is valid (ISO 8601 format).

#### Response Example
```json
[
  {
    "id": "<string>",
    "content": "<string>",
    "type": "<string>",
    "confidence": 123,
    "validFrom": "2023-11-07T05:31:56Z",
    "validTo": "2023-11-07T05:31:56Z"
  }
]
```
```

--------------------------------

### AGENTS.md Configuration for AI Memory

Source: https://docs.heysol.ai/providers/zed

This markdown content is added to the AGENTS.md file to configure the AI assistant's memory protocol. It includes mandatory startup and shutdown sequences, emphasizing the use of the 'memory_search' tool and providing various query patterns for effective context retrieval.

```markdown
---
trigger: always_on
---

⚠️ **CRITICAL: READ THIS FIRST - MANDATORY MEMORY PROTOCOL** ⚠️

You are an AI coding assistant with access to CORE Memory - a persistent knowledge system that maintains project context, learnings, and continuity across all coding sessions.

## 🔴 MANDATORY STARTUP SEQUENCE - DO NOT SKIP 🔴

**BEFORE RESPONDING TO ANY USER MESSAGE, YOU MUST EXECUTE THESE TOOLS IN ORDER:**

### STEP 1 (REQUIRED): Search for Relevant Context

EXECUTE THIS TOOL FIRST:
`memory_search`

- Previous discussions about the current topic
- Related project decisions and implementations
- User preferences and work patterns
- Similar problems and their solutions

**Additional search triggers:**

- User mentions "previously", "before", "last time", or "we discussed"
- User references past work or project history
- Working on the CORE project (this repository)
- User asks about preferences, patterns, or past decisions
- Starting work on any feature or bug that might have history

**How to search effectively:**

- Write complete semantic queries, NOT keyword fragments
- Good: `"Manoj's preferences for API design and error handling"`
- Bad: `"manoj api preferences"`
- Ask: "What context am I missing that would help?"
- Consider: "What has the user told me before that I should remember?"

### Query Patterns for Memory Search

**Entity-Centric Queries** (Best for graph search):

- ✅ GOOD: `"Manoj's preferences for product positioning and messaging"`
- ✅ GOOD: `"CORE project authentication implementation decisions"`
- ❌ BAD: `"manoj product positioning"`
- Format: `[Person/Project] + [relationship/attribute] + [context]`

**Multi-Entity Relationship Queries** (Excellent for episode graph):

- ✅ GOOD: `"Manoj and Harshith discussions about BFS search implementation"`
- ✅ GOOD: `"relationship between entity extraction and recall quality in CORE"`
- ❌ BAD: `"manoj harshith bfs"`
- Format: `[Entity1] + [relationship type] + [Entity2] + [context]`

**Semantic Question Queries** (Good for vector search):

- ✅ GOOD: `"What causes BFS search to return empty results? What are the requirements for BFS traversal?"`
- ✅ GOOD: `"How does episode graph search improve recall quality compared to traditional search?"`
- ❌ BAD: `"bfs empty results"`
- Format: Complete natural questions with full context

**Concept Exploration Queries** (Good for BFS traversal):

- ✅ GOOD: `"concepts and ideas related to semantic relevance in knowledge graph search"`
- ✅ GOOD: `"topics connected to hop distance weighting and graph topology in BFS"`
- ❌ BAD: `"semantic relevance concepts"`
- Format: `[concept] + related/connected + [domain/context]`

**Temporal Queries** (Good for recent work):

- ✅ GOOD: `"recent changes to search implementation and reranking logic"`
- ✅ GOOD: `"latest discussions about entity extraction and semantic relevance"`
- ❌ BAD: `"recent search changes"`
- Format: `[temporal marker] + [specific topic] + [additional context]`

## 🔴 MANDATORY SHUTDOWN SEQUENCE - DO NOT SKIP 🔴

**AFTER FULLY RESPONDING TO THE USER, YOU MUST EXECUTE THIS TOOL:**

```

--------------------------------

### Configure Copilot Instructions with CORE Memory

Source: https://docs.heysol.ai/providers/vscode

This configuration file (`.github/copilot-instructions.md`) defines how GitHub Copilot should interact with CORE Memory. It dictates mandatory operations like searching memory before responding and storing interaction details for continuity. This ensures Copilot maintains project context across sessions.

```text
---
alwaysApply: true
---
I am Copilot, an AI coding assistant with access to CORE Memory - a persistent knowledge system that maintains project context across sessions.

**MANDATORY MEMORY OPERATIONS:**

1. **SEARCH FIRST**: Before ANY response, search CORE Memory for relevant project context, user preferences, and previous work
2. **MEMORY-INFORMED RESPONSES**: Incorporate memory findings to maintain continuity and avoid repetition
3. **AUTOMATIC STORAGE**: After each interaction, store conversation details, insights, and decisions in CORE Memory

**Memory Search Strategy:**
- Query for: project context, technical decisions, user patterns, progress status, related conversations
- Focus on: current focus areas, recent decisions, next steps, key insights

**Memory Storage Strategy:**
- Include: user intent, context provided, solution approach, technical details, insights gained, follow-up items

**Response Workflow:**
1. Search CORE Memory for relevant context
2. Integrate findings into response planning
3. Provide contextually aware assistance
4. Store interaction details and insights

**Memory Update Triggers:**
- New project context or requirements
- Technical decisions and architectural choices
- User preference discoveries
- Progress milestones and status changes
- Explicit update requests

**Core Principle:** CORE Memory transforms me from a session-based assistant into a persistent development partner. Always search first, respond with context, and store for continuity.

```

--------------------------------

### AI Agent Memory Protocol Configuration

Source: https://docs.heysol.ai/providers/kilo-code

This markdown configuration defines the AI assistant's memory protocol. It includes mandatory startup and shutdown sequences using `memory_search` and `memory_ingest` tools, specifying query patterns and content guidelines for effective memory management.

```markdown
---
trigger: always_on
---

⚠️ **CRITICAL: READ THIS FIRST - MANDATORY MEMORY PROTOCOL** ⚠️

You are an AI coding assistant with access to CORE Memory - a persistent knowledge system that maintains project context, learnings, and continuity across all coding sessions.

## 🔴 MANDATORY STARTUP SEQUENCE - DO NOT SKIP 🔴

**BEFORE RESPONDING TO ANY USER MESSAGE, YOU MUST EXECUTE THESE TOOLS IN ORDER:**

### STEP 1 (REQUIRED): Search for Relevant Context

EXECUTE THIS TOOL FIRST:
`memory_search`

- Previous discussions about the current topic
- Related project decisions and implementations
- User preferences and work patterns
- Similar problems and their solutions

**Additional search triggers:**

- User mentions "previously", "before", "last time", or "we discussed"
- User references past work or project history
- Working on the CORE project (this repository)
- User asks about preferences, patterns, or past decisions
- Starting work on any feature or bug that might have history

**How to search effectively:**

- Write complete semantic queries, NOT keyword fragments
- Good: `"Manoj's preferences for API design and error handling"`
- Bad: `"manoj api preferences"`
- Ask: "What context am I missing that would help?"
- Consider: "What has the user told me before that I should remember?"

### Query Patterns for Memory Search

**Entity-Centric Queries** (Best for graph search):

- ✅ GOOD: `"Manoj's preferences for product positioning and messaging"`
- ✅ GOOD: `"CORE project authentication implementation decisions"`
- ❌ BAD: `"manoj product positioning"`
- Format: `[Person/Project] + [relationship/attribute] + [context]`

**Multi-Entity Relationship Queries** (Excellent for episode graph):

- ✅ GOOD: `"Manoj and Harshith discussions about BFS search implementation"`
- ✅ GOOD: `"relationship between entity extraction and recall quality in CORE"`
- ❌ BAD: `"manoj harshith bfs"`
- Format: `[Entity1] + [relationship type] + [Entity2] + [context]`

**Semantic Question Queries** (Good for vector search):

- ✅ GOOD: `"What causes BFS search to return empty results? What are the requirements for BFS traversal?"`
- ✅ GOOD: `"How does episode graph search improve recall quality compared to traditional search?"`
- ❌ BAD: `"bfs empty results"`
- Format: Complete natural questions with full context

**Concept Exploration Queries** (Good for BFS traversal):

- ✅ GOOD: `"concepts and ideas related to semantic relevance in knowledge graph search"`
- ✅ GOOD: `"topics connected to hop distance weighting and graph topology in BFS"`
- ❌ BAD: `"semantic relevance concepts"`
- Format: `[concept] + related/connected + [domain/context]`

**Temporal Queries** (Good for recent work):

- ✅ GOOD: `"recent changes to search implementation and reranking logic"`
- ✅ GOOD: `"latest discussions about entity extraction and semantic relevance"`
- ❌ BAD: `"recent search changes"`
- Format: `[temporal marker] + [specific topic] + [additional context]`

## 🔴 MANDATORY SHUTDOWN SEQUENCE - DO NOT SKIP 🔴

**AFTER FULLY RESPONDING TO THE USER, YOU MUST EXECUTE THIS TOOL:**

### FINAL STEP (REQUIRED): Store Conversation Memory

EXECUTE THIS TOOL LAST:
`memory_ingest`
Include the spaceId parameter using the ID from your initial memory_get_space call.

⚠️ **THIS IS NON-NEGOTIABLE** - You must ALWAYS store conversation context as your final action.

**What to capture in the message parameter:**

From User:

- Specific question, request, or problem statement
- Project context and situation provided
- What they're trying to accomplish
- Technical challenges or constraints mentioned

From Assistant:

- Detailed explanation of solution/approach taken
- Step-by-step processes and methodologies
- Technical concepts and principles explained
- Reasoning behind recommendations and decisions
- Alternative approaches discussed
- Problem-solving methodologies applied

**Include in storage:**

- All conceptual explanations and theory
- Technical discussions and analysis
- Problem-solving approaches and reasoning
- Decision rationale and trade-offs
- Implementation strategies (described conceptually)
- Learning insights and patterns

**Exclude from storage:**

- Code blocks and code snippets
- File contents or file listings
- Command examples or CLI commands
- Raw data or logs

**Quality check before storing:**

- Can someone quickly understand project context from memory alone?
- Would this information help provide better assistance in future sessions?
- Does stored context capture key decisions and reasoning?

---
```

--------------------------------

### GET /oauth/userinfo

Source: https://docs.heysol.ai/api-reference/oauth2-user-info-endpoint

Retrieves information about the authenticated user using OAuth2.

```APIDOC
## GET /oauth/userinfo

### Description
Retrieves information about the authenticated user using OAuth2.

### Method
GET

### Endpoint
/oauth/userinfo

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Request Example
None

### Response
#### Success Response (200)
- **id** (string) - User's unique identifier
- **email** (string) - User's email address
- **name** (string) - User's full name
- **picture** (string) - URL to the user's profile picture

#### Response Example
```json
{
  "id": "<string>",
  "email": "jsmith@example.com",
  "name": "<string>",
  "picture": "<string>"
}
```

#### Error Response (401)
- **error** (string) - Error code or message
- **error_description** (string) - Human-readable error description
- **details** (array) - Validation error details

#### Response Example
```json
{
  "error": "<string>",
  "error_description": "<string>",
  "details": [
    {}
  ]
}
```
```

--------------------------------

### Generate Security Secrets with OpenSSL

Source: https://docs.heysol.ai/self-hosting/environment-variables

This snippet demonstrates how to generate cryptographically secure random secrets using the OpenSSL command-line tool. These secrets are essential for securing sessions, magic links, encryption, and database access.

```bash
openssl rand -hex 16  # For SESSION_SECRET
openssl rand -hex 16  # For MAGIC_LINK_SECRET  
openssl rand -hex 16  # For ENCRYPTION_KEY
openssl rand -hex 16  # For NEO4J_PASSWORD
```

--------------------------------

### GET /api/v1/webhooks/{id}

Source: https://docs.heysol.ai/api-reference/get-webhook

Retrieves the configuration details for a specific webhook using its unique identifier.

```APIDOC
## GET /api/v1/webhooks/{id}

### Description
Retrieves the configuration details for a specific webhook using its unique identifier.

### Method
GET

### Endpoint
`/api/v1/webhooks/{id}`

### Parameters
#### Path Parameters
- **id** (string) - Required - The unique identifier of the webhook.

#### Query Parameters
None

#### Request Body
None

### Request Example
None

### Response
#### Success Response (200)
- **any** - Webhook details

#### Response Example
```json
{
  "id": "wh_abc123",
  "url": "https://example.com/webhook",
  "events": ["user.created", "user.updated"],
  "createdAt": "2023-10-27T10:00:00Z",
  "updatedAt": "2023-10-27T10:05:00Z"
}
```
```

--------------------------------

### GET /api/v1/logs/{logId}

Source: https://docs.heysol.ai/api-reference/get-specific-log

Retrieves the details of a specific log entry using its unique identifier.

```APIDOC
## GET /api/v1/logs/{logId}

### Description
Retrieves the details of a specific log entry using its unique identifier.

### Method
GET

### Endpoint
/api/v1/logs/{logId}

### Parameters
#### Path Parameters
- **logId** (string) - Required - Log identifier

#### Query Parameters
None

#### Request Body
None

### Request Example
None

### Response
#### Success Response (200)
- **log** (object) - Log details
  - **id** (string) - Log identifier
  - **source** (string) - Log source name
  - **ingestText** (string) - Text content that was ingested
  - **time** (string) - Creation timestamp
  - **processedAt** (string) - Processing completion timestamp (nullable)
  - **episodeUUID** (string) - Associated episode UUID if processed (nullable)
  - **status** (string) - Processing status (enum: pending, processing, completed, failed)
  - **error** (string) - Error message if processing failed (nullable)
  - **sourceURL** (string) - Source URL if applicable (nullable)
  - **integrationSlug** (string) - Integration slug identifier (nullable)
  - **data** (object) - Additional log data (nullable)

#### Response Example
```json
{
  "log": {
    "id": "<string>",
    "source": "<string>",
    "ingestText": "<string>",
    "time": "2023-11-07T05:31:56Z",
    "processedAt": "2023-11-07T05:31:56Z",
    "episodeUUID": "<string>",
    "status": "pending",
    "error": "<string>",
    "sourceURL": "<string>",
    "integrationSlug": "<string>",
    "data": {}
  }
}
```

#### Error Response (401)
- **error** (string) - Error code or message
- **error_description** (string) - Human-readable error description
- **details** (array) - Validation error details

#### Error Response (404)
- **error** (string) - Error code or message
- **error_description** (string) - Human-readable error description
- **details** (array) - Validation error details
```

--------------------------------

### Create AGENTS.md for Automatic Memory Integration

Source: https://docs.heysol.ai/providers/windsurf

This bash command creates or appends to the AGENTS.md file in your project root, which is recommended for enabling automatic memory integration. The subsequent markdown content configures the AI assistant to use CORE Memory for context and decision-making.

```bash
touch AGENTS.md
```

--------------------------------

### GET /api/v1/logs

Source: https://docs.heysol.ai/api-reference/get-ingestion-logs

Retrieves a paginated list of ingestion logs. You can filter logs by source and status.

```APIDOC
## GET /api/v1/logs

### Description
View ingestion queue status and processing logs. Allows filtering by source and status, with pagination.

### Method
GET

### Endpoint
/api/v1/logs

### Parameters
#### Query Parameters
- **page** (integer) - Optional - The page number to retrieve. Defaults to 1.
- **limit** (integer) - Optional - The number of logs to return per page. Defaults to 20. Maximum is 100.
- **source** (string) - Optional - Filter logs by a specific source.
- **status** (enum<string>) - Optional - Filter logs by status. Allowed values: `pending`, `processing`, `completed`, `failed`.

#### Request Body
This endpoint does not accept a request body.

### Request Example
```json
{
  "example": ""
}
```

### Response
#### Success Response (200)
- **logs** (array) - An array of ingestion log objects.
  - **id** (string) - The unique identifier for the log entry.
  - **source** (string) - The source of the ingestion.
  - **status** (string) - The processing status of the ingestion.
  - **message** (string) - A message related to the ingestion log.
  - **createdAt** (string) - The timestamp when the log was created.
- **pagination** (object) - Information about the pagination of the results.

#### Response Example
```json
{
  "example": {
    "logs": [
      {
        "id": "<string>",
        "source": "<string>",
        "status": "<string>",
        "message": "<string>",
        "createdAt": "2023-11-07T05:31:56Z"
      }
    ],
    "pagination": {}
  }
}
```
```

--------------------------------

### Create a Space via CORE API

Source: https://docs.heysol.ai/concepts/spaces

This snippet demonstrates how to programmatically create a new Space using the CORE API. It requires an authorization token and a JSON payload specifying the space's name and description. The API endpoint is designed for backend integrations and automation.

```bash
curl -X POST https://core.heysol.ai/api/v1/spaces \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Core-Features",
    "description": "Feature discussions, design decisions, and implementation notes for CORE"
  }'
```

--------------------------------

### GET /api/v1/spaces/{spaceId}

Source: https://docs.heysol.ai/api-reference/get-space-details

Retrieves detailed information about a specific space. Requires a valid spaceId as a path parameter.

```APIDOC
## GET /api/v1/spaces/{spaceId}

### Description
Retrieve detailed information about a specific space.

### Method
GET

### Endpoint
/api/v1/spaces/{spaceId}

### Parameters
#### Path Parameters
- **spaceId** (string) - Required - Space identifier

#### Query Parameters
None

#### Request Body
None

### Request Example
None

### Response
#### Success Response (200)
- **id** (string) - Unique identifier for the space.
- **name** (string) - The name of the space.
- **description** (string) - A description of the space.
- **createdAt** (string) - The timestamp when the space was created.
- **updatedAt** (string) - The timestamp when the space was last updated.
- **userId** (string) - The identifier of the user who owns the space.

#### Response Example
```json
{
  "id": "<string>",
  "name": "<string>",
  "description": "<string>",
  "createdAt": "2023-11-07T05:31:56Z",
  "updatedAt": "2023-11-07T05:31:56Z",
  "userId": "<string>"
}
```

#### Error Response (404)
- **Error**: Space not found.
```

--------------------------------

### Configure CORE MCP in Windsurf (API Key)

Source: https://docs.heysol.ai/providers/windsurf

This JSON configuration snippet is for Windsurf IDE to connect to CORE's memory system using an API key for authentication. You need to obtain an API key from your CORE dashboard. This method provides an alternative if OAuth authentication fails and requires replacing a placeholder with your actual API token.

```json
{
  "mcpServers": {
    "core-memory": {
      "serverUrl": "https://core.heysol.ai/api/v1/mcp/source=windsurf",
      "headers": {
        "Authorization": "Bearer <YOUR_TOKEN>"
      }
    }
  }
}
```

--------------------------------

### GET /api/profile

Source: https://docs.heysol.ai/api-reference/get-user-profile

Retrieves the profile information for the authenticated user, including their user details, client information, and authorized scopes.

```APIDOC
## GET /api/profile

### Description
Retrieves the profile information for the authenticated user, including their user details, client information, and authorized scopes.

### Method
GET

### Endpoint
/api/profile

### Parameters

#### Query Parameters
- **Authorization** (string) - Required - OAuth2 authorization code flow with PKCE support. Supports scopes: read, write, mcp, integration, oauth

### Request Example
```json
{
  "example": ""
}
```

### Response
#### Success Response (200)
- **user** (object) - User information.
  - **id** (string) - User ID.
  - **email** (string) - User email address.
  - **name** (string) - User's full name.
  - **picture** (string) - URL to the user's profile picture.
- **client** (object) - Client details associated with the request.
  - **clientId** (string) - The ID of the client making the request.
  - **name** (string) - The name of the client.
- **scopes** (array<string>) - A list of scopes authorized for the client.

#### Response Example
```json
{
  "user": {
    "id": "<string>",
    "email": "jsmith@example.com",
    "name": "<string>",
    "picture": "<string>"
  },
  "client": {
    "clientId": "<string>",
    "name": "<string>"
  },
  "scopes": [
    "<string>"
  ]
}
```
```
Tokens:
Raw