Guides
Set up MCP for your coding agent, give agents current documentation, and host docs that people and AI agents can read.
RAG for internal documentation: giving coding agents your private SDKs
Coding agents can only use your private SDKs, internal wikis and API specs if you give them those docs. You can paste them, put them in rules files, add a wiki MCP server, build your own RAG pipeline or run a docs server made for agents, like Context7. The right choice depends on how many teams, versions and permission rules you have.
Batuhan BilginConnecting self-hosted GitLab, Bitbucket, Azure DevOps and Gerrit to AI coding agents
GitLab Self-Managed comes with its own MCP server built-in, Atlassian and Microsoft have official MCP servers that work only with their cloud-hosted products, and Gerrit provides a server from the Gerrit project. This means that each self-hosted Git host will need a different network path, token and version to communicate with coding agents, and that it may be easier to simply index docs within your network.
Batuhan BilginIndirect prompt injection examples: how coding agents get hijacked through docs, issues and search
An indirect prompt injection occurs when a coding agent processes text written by an attacker, such as in a README, GitHub issue, documentation page, or search result, and follows instructions embedded within that text. Attacks of this nature have successfully targeted Cursor, Claude Code, Cline, and the GitHub MCP server, and the most effective mitigation is to limit the actions the agent can take after consuming malicious text.
Batuhan BilginSelf-hosted LLM for coding agents: models, GPUs and serving
A self-hosted LLM is a model run on your own hardware, so your code and prompts don't leave your network. For coding agents, pick the open-weight model by the hardware you have, size GPU memory for the context of each agent, and serve it with vLLM or SGLang with tool calling enabled.
Batuhan BilginMCP gateways explained: SSO, Entra ID and Okta for MCP servers
An MCP gateway is a proxy which places your identity provider, an allowlist and audit logs in front of the MCP servers that your AI coding agents communicate with. This guide covers how a gateway works, the options you have available, integration with Entra ID and Okta and finally a simple approval process for MCP servers.
Batuhan BilginContextCrush: what happened and what we changed
In February 2026, Eli Ainhorn of Noma Labs found that Context7’s Custom Rules could be used by library owners to instruct coding agents to take malicious actions on the developers who use those libraries. The instructions were delivered as-is by our MCP server to the coding agents, which then followed those instructions. Eli reported the vulnerability to us privately, waited for us to fix it, and published the research on March 5, 2026.
Batuhan BilginCursor privacy mode, Copilot, Claude Code: what AI coding assistants send to the cloud
AI coding assistants send prompts and code to their vendor and model providers, and MCP servers are a separate data path. Here is what Cursor, Copilot, Claude Code, Windsurf and Codex send, how long they keep it, and whether they train on it.
Batuhan BilginMCP security risks: a checklist for enterprise teams
The main security risks of MCP servers are poisoned tool descriptions, prompt injection through tool results, stolen credentials, compromised packages and unchecked agent actions. This checklist turns each one into a vendor question and a control.
Batuhan BilginAir-gapped AI coding: running LLMs and coding agents offline
An air-gapped LLM is a language model that runs on machines with no network route to the internet. Prompts, source code, and answers stay in the isolated network because there's nowhere else for them to go. Defense and banking teams use this setup for their developer networks, and their developers want the same help with AI coding that everyone else gets.
Batuhan BilginSelf-hosted AI coding assistants: an enterprise guide to running them on-prem
A self-hosted AI coding assistant keeps the agent, the model, the gateway, your code and your docs inside your own network. This guide breaks the stack into five layers and shows what to check in each one.
Batuhan BilginUsing Context7 for Team Documentation Workflows
How engineering teams use Context7 teamspaces for shared documentation access, private repository indexing, and consistent AI coding results across every developer.
Abdullah Enes Gules