LangChain is a framework for building software agents and applications powered by large language models, using reusable components and integrations. Developers use it to connect models, tools, and other services when creating AI applications and agent workflows. The catalogue includes MCP integrations and instructions related to LangChain.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/langchain-ai/langchainWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/mcp/langchain-ai/langchain/docs-langchain)<a href="https://agentmods.dev/mcp/langchain-ai/langchain/docs-langchain"><img src="https://agentmods.dev/badge/mcp/langchain-ai/langchain/docs-langchain/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/mcp/langchain-ai/langchain/docs-langchain"><img src="https://agentmods.dev/badge/mcp/langchain-ai/langchain/docs-langchain.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
docs-langchain scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
5 near-identical copies found in the catalogue:
- docs-langchain — 100% identical, 0 lines differ
- docs-langchain — 100% identical, 0 lines differ
- docs-langchain — 100% identical, 0 lines differ
- docs-langchain — 100% identical, 0 lines differ
- langchain-docs — 88% identical, 2 lines differ
What it actually says
{
"docs-langchain": {
"type": "http",
"url": "https://docs.langchain.com/mcp"
}
}What else .mcp.json configures
This page is one entry in a file that holds 2. Installing the file brings all of them; each is measured and scanned on its own page.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 6 lines scan A 8f9f7b2072a4
docs-langchain is an MCP server published in the GitHub repository langchain-ai/langchain (147,886 stars, last pushed today), licensed MIT. Its token cost is not measured: an MCP server costs its tool schemas, not its config file. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other mcp servers, from other repositories
docs-langchain
MCP server "docs-langchain", hosted remotely at docs.langchain.com, as configured in srtab/daiv.
liter-llm
MCP server "liter-llm" as configured in xberg-io/liter-llm. Launched with ./scripts/mcp-launch.sh mcp --transport stdio.
mcp-server
Query Spanlens LLM observability from Cursor, Claude Desktop, or Continue via MCP. Runs locally from the @spanlens/mcp-server npm package. Needs 2 environment variables to run.
webfetch
MCP server "webfetch" as configured in firish/webfetch. Runs locally from the webfetch-llm@latest Python package.
vox-mcp
Multi-model AI gateway for MCP clients — routes prompts to Gemini, OpenAI, Anthropic, xAI, DeepSeek, Moonshot, OpenRouter, Cloudflare AI Gateway, Vercel AI Gateway, and local models with conversation memory. Runs locally from the vox-mcp Python package. Needs 19 environment variables to run.
tooltrim
Drop-in compression for LLM agent tool outputs. Shrink bloated HTML/JSON/log results before they re-enter context — cut tokens, stay on-task, keep full output retrievable. Runs locally from the tooltrim Python package.