Library Docs MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Library Docs MCP Server how do I use LangChain's new agents API?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Library Docs MCP Server
This is an MCP (Model Context Protocol) server that allows you to search and fetch documentation for popular libraries like Langchain, Llama-Index, MCP, and OpenAI using the Serper API.
Features
Search library documentation using a natural language query.
Supports Langchain, Llama-Index, MCP, and OpenAI (Update the code to add other libraries).
Uses the
Serper APIto perform site-specific searches.Parses and returns the documentation using
BeautifulSoup.Provides updated documentation – useful for LLM models with knowledge cut-off dates.
Related MCP server: docpilot-mcp
Why Use This Server with LLMs?
Many LLM models, including those used in Claude Desktop and similar platforms, have a knowledge cut-off date and may not have access to the latest library documentation. This MCP server solves that problem by:
Fetching real-time documentation from official sources.
Providing up-to-date information for development and troubleshooting.
Improving the accuracy and relevance of responses when working with new library updates.
Setting Up with Claude Desktop
To use this server with Claude Desktop, update the claude_desktop_config.json file with the following configuration:
{
"mcpServers": {
"docs-mcp-server": {
"command": "C:\\Users\\Vikram\\.local\\bin\\uv.exe",
"args": [
"run",
"--with",
"mcp[cli]",
"mcp",
"run",
"F:\\My Projects\\AI\\docs-mcp-server\\server.py"
]
}
}
}Available Tools
1 toolget_docsC
Search the docs for a given query and library.
Supports langchain, llama-index, mcp, and openai.
Args:
query: The query to search for (e.g. "Chroma DB")
library: The library to search in (e.g. "langchain")
Returns:
Text from the docs
Inputs: query (required), library (required).
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 1 tool
With only one tool, there is no possibility of confusion or overlap between tools. The tool has a single, clear purpose: searching documentation for specific libraries.
The single tool name 'get_docs' follows a clear verb_noun pattern, making it predictable and readable. There are no other tools to compare against, so consistency is inherently perfect.
A single tool for a documentation search server feels too thin for the apparent scope, which involves multiple libraries (langchain, llama-index, mcp, openai). This minimal set may limit functionality and force agents to rely heavily on this one tool for all tasks.
The tool surface is severely incomplete for a documentation server. While it supports search, there are obvious gaps such as listing available libraries, browsing documentation sections, or getting metadata about docs. This will likely cause agent failures when more nuanced interactions are needed.
Maintenance
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