### Run Tests

Source: https://github.com/lablnet/langgraph-checkpoint-mongodb/blob/main/README.md

Installs dependencies and runs project tests using pnpm.

```bash
pnpm i
pnpm run test
```

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

### Install langgraph-checkpoint-mongodb

Source: https://github.com/lablnet/langgraph-checkpoint-mongodb/blob/main/README.md

Installs the langgraph-checkpoint-mongodb package using pnpm or npm.

```bash
pnpm add langgraph-checkpoint-mongodb
# or: npm i langgraph-checkpoint-mongodb
```

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

### Complete LangGraph Integration Example with MongoCheckpointSaver

Source: https://context7.com/lablnet/langgraph-checkpoint-mongodb/llms.txt

Full example demonstrating how to integrate MongoCheckpointSaver with a LangGraph application for persistent, resumable agent conversations. This includes setting up a singleton pattern for checkpointer management and handling connection lifecycle. It requires MongoDB connection details and LangGraph dependencies.

```typescript
import { MongoClient } from 'mongodb'
import type { BaseCheckpointSaver } from '@langchain/langgraph' 
import { MongoCheckpointSaver } from 'langgraph-checkpoint-mongodb'

// Singleton pattern for checkpointer management
let saver: BaseCheckpointSaver | null = null
let client: MongoClient | null = null

export async function getCheckpointer(): Promise<BaseCheckpointSaver> {
  if (saver) return saver

  const uri = process.env.MONGODB_URI!
  const dbName = process.env.MONGODB_DB || 'langgraph'

  client = await MongoClient.connect(uri)
  saver = new MongoCheckpointSaver(client, dbName)

  return saver
}

export async function closeCheckpointer(): Promise<void> {
  if (client) {
    await client.close()
    client = null
    saver = null
  }
}

// Usage with LangGraph (pseudocode)
async function runAgent() {
  const checkpointer = await getCheckpointer()

  // Create your LangGraph with the checkpointer
  // const graph = createGraph({ checkpointer })

  // Run with a thread ID for persistence
  // const result = await graph.invoke(input, {
  //   configurable: {
  //     thread_id: 'user-123',
  //     checkpoint_ns: 'default'
  //   }
  // })
}

// Cleanup on shutdown
process.on('SIGTERM', async () => {
  await closeCheckpointer()
  process.exit(0)
})
```

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

### Initialize MongoCheckpointSaver (JavaScript CJS)

Source: https://github.com/lablnet/langgraph-checkpoint-mongodb/blob/main/README.md

A minimal example of initializing MongoCheckpointSaver in JavaScript (CJS). It connects to MongoDB and creates a saver instance.

```javascript
const { MongoClient } = require('mongodb')
const { MongoCheckpointSaver } = require('langgraph-checkpoint-mongodb')

(async () => {
  const client = await MongoClient.connect(process.env.MONGODB_URI)
  const saver = new MongoCheckpointSaver(client, process.env.MONGODB_DB)
  // use saver
})()
```

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

### Build Project

Source: https://github.com/lablnet/langgraph-checkpoint-mongodb/blob/main/README.md

Builds the project using the pnpm run build command.

```bash
pnpm run build
```

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

### Initialize MongoCheckpointSaver

Source: https://context7.com/lablnet/langgraph-checkpoint-mongodb/llms.txt

Instantiates the MongoDB checkpointer. Supports basic connection strings or custom serialization (serde) for advanced data handling.

```typescript
import { MongoClient } from 'mongodb'
import { MongoCheckpointSaver } from 'langgraph-checkpoint-mongodb'

// Basic usage without custom serde
const client = await MongoClient.connect(process.env.MONGODB_URI!)
const saver = new MongoCheckpointSaver(client, 'my_langgraph_db')

// With custom JSON serde for explicit serialization control
const jsonSerde = {
  async dumpsTyped(value: unknown): Promise<[string, Uint8Array]> {
    const buf = Buffer.from(JSON.stringify(value))
    return ['json', new Uint8Array(buf)]
  },
  async loadsTyped(_type: string, bytes: Uint8Array): Promise<unknown> {
    const str = Buffer.from(bytes).toString('utf-8')
    return JSON.parse(str)
  },
}

const saverWithSerde = new MongoCheckpointSaver(client, 'my_langgraph_db', jsonSerde)
```

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

### Initialize MongoCheckpointSaver with Custom Serde (TypeScript ESM)

Source: https://github.com/lablnet/langgraph-checkpoint-mongodb/blob/main/README.md

Shows how to use MongoCheckpointSaver with a custom serde for efficient typed storage in TypeScript (ESM). It defines `dumpsTyped` and `loadsTyped` functions.

```javascript
import { MongoClient } from 'mongodb'
import { MongoCheckpointSaver } from 'langgraph-checkpoint-mongodb'

const serde = {
  async dumpsTyped(v) {
    const buf = Buffer.from(JSON.stringify(v))
    return ['json', new Uint8Array(buf)] as const
  },
  async loadsTyped(_t, b) {
    return JSON.parse(Buffer.from(b).toString('utf8'))
  },
}

const client = await MongoClient.connect(process.env.MONGODB_URI!)
const saver = new MongoCheckpointSaver(client, process.env.MONGODB_DB!, serde)
// provide `saver` to your LangGraph app
```

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

### Initialize MongoCheckpointSaver (TypeScript ESM)

Source: https://github.com/lablnet/langgraph-checkpoint-mongodb/blob/main/README.md

Demonstrates simple usage of MongoCheckpointSaver in TypeScript (ESM) without a custom serde. It connects to MongoDB and initializes the saver.

```typescript
import {
  MongoClient
} from 'mongodb'
import type { BaseCheckpointSaver } from '@langchain/langgraph'
import { MongoCheckpointSaver } from 'langgraph-checkpoint-mongodb'

let saver: BaseCheckpointSaver | null = null

export async function getCheckpointer(): Promise<BaseCheckpointSaver> {
  if (saver) return saver
  const dbName = process.env.MONGODB_DB!
  const uri = process.env.MONGODB_URI!
  const client = await MongoClient.connect(uri)
  saver = new MongoCheckpointSaver(client, dbName)
  return saver
}

export async function closeCheckpointer() {
  if (!saver) return
  // if you kept a client reference, close it here
  saver = null
}
```

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

### List Checkpoints with Pagination and Filtering using MongoCheckpointSaver

Source: https://context7.com/lablnet/langgraph-checkpoint-mongodb/llms.txt

Provides an asynchronous iterator to list checkpoints for a thread, sorted by timestamp. Supports pagination via `limit`, filtering by `before` a specific checkpoint, and custom query filters. Useful for historical analysis or state restoration.

```typescript
import { MongoClient } from 'mongodb'
import { MongoCheckpointSaver } from 'langgraph-checkpoint-mongodb'

const client = await MongoClient.connect(process.env.MONGODB_URI!)
const saver = new MongoCheckpointSaver(client, 'langgraph_db', jsonSerde)

const config = {
  configurable: {
    thread_id: 'conversation-789',
    checkpoint_ns: 'chat'
  }
}

console.log('All checkpoints:')
for await (const item of saver.list(config)) {
  console.log(`  - ${item.checkpoint.id} at ${item.checkpoint.ts}`)
}

console.log('
First 5 checkpoints:')
for await (const item of saver.list(config, { limit: 5 })) {
  console.log(`  - ${item.checkpoint.id}`)
}

const beforeConfig = {
  configurable: {
    thread_id: 'conversation-789',
    checkpoint_ns: 'chat',
    checkpoint_id: 'cp-5'
  }
}

console.log('
Checkpoints before cp-5:')
for await (const item of saver.list(config, { before: beforeConfig, limit: 3 })) {
  console.log(`  - ${item.checkpoint.id}`)
}
```

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

### Method: put

Source: https://context7.com/lablnet/langgraph-checkpoint-mongodb/llms.txt

Stores a checkpoint snapshot in MongoDB. This method persists the current state of the graph, allowing the agent to resume from this specific point later.

```APIDOC
## POST /put

### Description
Stores a checkpoint snapshot in MongoDB. Returns a RunnableConfig that references the exact checkpoint, allowing LangGraph to resume from this state.

### Method
POST

### Parameters
#### Request Body
- **config** (object) - Required - Contains thread_id and checkpoint_ns.
- **checkpoint** (object) - Required - The checkpoint object matching LangGraph's Checkpoint interface.
- **metadata** (object) - Required - Metadata associated with the checkpoint.
- **newVersions** (object) - Required - Channel versions for the checkpoint.

### Request Example
{
  "config": { "configurable": { "thread_id": "user-123", "checkpoint_ns": "default" } },
  "checkpoint": { "id": "cp-001", "ts": "2023-10-27T10:00:00Z" },
  "metadata": { "source": "input" },
  "newVersions": { "messages": 1 }
}

### Response
#### Success Response (200)
- **RunnableConfig** (object) - The configuration object updated with the checkpoint_id.

#### Response Example
{
  "configurable": {
    "thread_id": "user-123",
    "checkpoint_ns": "default",
    "checkpoint_id": "cp-001"
  }
}
```

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

### Retrieve Full Checkpoint Tuple with MongoCheckpointSaver

Source: https://context7.com/lablnet/langgraph-checkpoint-mongodb/llms.txt

Retrieves a complete checkpoint tuple, including the checkpoint, metadata, pending writes, and configuration. This is essential for restoring agent state in LangGraph. The method handles deserialization and returns all relevant data for a given thread and namespace.

```typescript
import { MongoClient } from 'mongodb'
import { MongoCheckpointSaver } from 'langgraph-checkpoint-mongodb'

const client = await MongoClient.connect(process.env.MONGODB_URI!)
const saver = new MongoCheckpointSaver(client, 'langgraph_db', jsonSerde)

const config = {
  configurable: {
    thread_id: 'agent-session-456',
    checkpoint_ns: 'workflow'
  }
}

const tuple = await saver.getTuple(config)

if (tuple) {
  console.log('Checkpoint:', tuple.checkpoint.id)
  console.log('Config:', tuple.config.configurable)
  console.log('Metadata:', tuple.metadata)
  console.log('Pending writes count:', tuple.pendingWrites?.length)

  tuple.pendingWrites?.forEach(([taskId, channel, value]) => {
    console.log(`  Task ${taskId} -> ${channel}:`, value)
  })
}
```

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

### Store Checkpoint with put()

Source: https://context7.com/lablnet/langgraph-checkpoint-mongodb/llms.txt

Persists a checkpoint snapshot to MongoDB. Returns a configuration object containing the checkpoint ID for future state resumption.

```typescript
import { MongoClient } from 'mongodb'
import { MongoCheckpointSaver } from 'langgraph-checkpoint-mongodb'

const client = await MongoClient.connect(process.env.MONGODB_URI!)
const saver = new MongoCheckpointSaver(client, 'langgraph_db', jsonSerde)

const config = {
  configurable: {
    thread_id: 'user-session-123',
    checkpoint_ns: 'default'
  }
}

const checkpoint = {
  v: 1,
  id: 'checkpoint-001',
  ts: new Date().toISOString(),
  channel_values: { messages: ['Hello', 'World'] },
  channel_versions: { messages: 1 },
  versions_seen: {},
  pending_sends: []
}

const metadata = { source: 'input', step: 0, parents: {} }
const newVersions = { messages: 1 }

const savedConfig = await saver.put(config, checkpoint, metadata, newVersions)
console.log('Saved checkpoint ID:', savedConfig.configurable?.checkpoint_id)
```

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

### Retrieve Latest Checkpoint with MongoCheckpointSaver

Source: https://context7.com/lablnet/langgraph-checkpoint-mongodb/llms.txt

Fetches the most recent checkpoint for a specified thread and namespace using MongoCheckpointSaver. It deserializes the checkpoint using the configured serde. Returns undefined if no checkpoint is found.

```typescript
import { MongoClient } from 'mongodb'
import { MongoCheckpointSaver } from 'langgraph-checkpoint-mongodb'

const client = await MongoClient.connect(process.env.MONGODB_URI!)
const saver = new MongoCheckpointSaver(client, 'langgraph_db', jsonSerde)

const config = {
  configurable: {
    thread_id: 'user-session-123',
    checkpoint_ns: 'default'
  }
}

const checkpoint = await saver.get(config)

if (checkpoint) {
  console.log('Checkpoint ID:', checkpoint.id)
  console.log('Timestamp:', checkpoint.ts)
  console.log('Channel values:', checkpoint.channel_values)
} else {
  console.log('No checkpoint found for this thread')
}
```

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

### Method: putWrites

Source: https://context7.com/lablnet/langgraph-checkpoint-mongodb/llms.txt

Stores pending writes associated with a specific checkpoint. These are serialized channel updates that have not yet been committed to a full checkpoint.

```APIDOC
## POST /putWrites

### Description
Stores pending writes associated with a checkpoint. Each write is stored with its channel name, task ID, and serialized value.

### Method
POST

### Parameters
#### Request Body
- **config** (object) - Required - The config object containing the checkpoint reference.
- **writes** (array) - Required - Array of [channel_name, value] tuples.
- **taskId** (string) - Required - The unique ID of the task performing the write.

### Request Example
{
  "config": { "configurable": { "checkpoint_id": "cp-001" } },
  "writes": [["messages", { "role": "user" }]],
  "taskId": "task-abc-123"
}

### Response
#### Success Response (200)
- **void** - Returns nothing upon successful storage.

#### Response Example
{
  "status": "success"
}
```

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

### Store Pending Writes with putWrites()

Source: https://context7.com/lablnet/langgraph-checkpoint-mongodb/llms.txt

Saves pending channel updates associated with a specific checkpoint. This is used to track state changes that have not yet been finalized in a checkpoint.

```typescript
import { MongoClient } from 'mongodb'
import { MongoCheckpointSaver } from 'langgraph-checkpoint-mongodb'

const client = await MongoClient.connect(process.env.MONGODB_URI!)
const saver = new MongoCheckpointSaver(client, 'langgraph_db', jsonSerde)

const config = {
  configurable: {
    thread_id: 'agent-session-456',
    checkpoint_ns: 'workflow'
  }
}

const checkpoint = {
  v: 1,
  id: 'cp-workflow-1',
  ts: new Date().toISOString(),
  channel_values: {},
  channel_versions: {},
  versions_seen: {},
  pending_sends: []
}

const savedConfig = await saver.put(config, checkpoint, { source: 'input', step: 0, parents: {} }, {})

const writes = [
  ['messages', { role: 'user', content: 'What is the weather?' }],
  ['tool_calls', { name: 'get_weather', args: { location: 'NYC' } }]
]

await saver.putWrites(savedConfig, writes, 'task-abc-123')
console.log('Pending writes stored successfully')
```

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

### Clear All Checkpoints with MongoCheckpointSaver

Source: https://context7.com/lablnet/langgraph-checkpoint-mongodb/llms.txt

Wipes all checkpoints, writes, and versions from the MongoDB database. This operation should be used with caution as it removes all stored state for all threads. It requires a MongoClient instance and a MongoCheckpointSaver configured with a database name and optionally a serde object.

```typescript
import { MongoClient } from 'mongodb'
import { MongoCheckpointSaver } from 'langgraph-checkpoint-mongodb'

const client = await MongoClient.connect(process.env.MONGODB_URI!)
const saver = new MongoCheckpointSaver(client, 'langgraph_db', jsonSerde)

// Clear all data (use with caution!)
await saver.clearAll()
console.log('All checkpoint data cleared')
```

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

### Delete Thread Data with MongoCheckpointSaver

Source: https://context7.com/lablnet/langgraph-checkpoint-mongodb/llms.txt

Removes all checkpoints, writes, and version data associated with a specific thread ID and namespace. This method is useful for cleaning up old conversations or resetting an agent's state entirely. It confirms deletion by attempting to retrieve a checkpoint afterward.

```typescript
import { MongoClient } from 'mongodb'
import { MongoCheckpointSaver } from 'langgraph-checkpoint-mongodb'

const client = await MongoClient.connect(process.env.MONGODB_URI!)
const saver = new MongoCheckpointSaver(client, 'langgraph_db', jsonSerde)

await saver.deleteThread('user-session-123', 'default')
console.log('Thread data deleted')

const config = {
  configurable: {
    thread_id: 'user-session-123',
    checkpoint_ns: 'default'
  }
}
const checkpoint = await saver.get(config)
console.log('Checkpoint after deletion:', checkpoint)
```

=== COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.