What does the mcp-server-python do?
It serves as a bridge between your documentation (managed by Inkeep) and an MCP client, allowing AI assistants to retrieve relevant product content using the `search-product-content` tool.
MCP Server Python
@inkeep
基本信息
关于 MCP Server Python
Inkeep MCP Server
MCP Server Python 配置
MCP Server Python 工具
工具列表暂未提供
当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
概览
What is mcp-server-python?
mcp-server-python is an MCP server that provides retrieval-augmented generation (RAG) over your documentation and product content using an Inkeep account. It's designed for developers who want to query their own product docs through the Model Context Protocol.
How to use mcp-server-python?
Clone the repository, set up a Python virtual environment with uv, and install dependencies. Obtain an API key from the Inkeep Dashboard, then add the server configuration to your claude_desktop_config.json file, specifying the absolute project path, API key, and base URL.
Key features of mcp-server-python
- RAG powered by your docs and product content.
- Uses Inkeep’s API for retrieval.
- Single tool:
search-product-content. - Requires an Inkeep account and API key.
- Runs locally via
uvPython project manager. - Integrates with Claude Desktop via MCP.
Use cases of mcp-server-python
- Accessing product documentation through conversational queries in Claude Desktop.
- Providing context-aware answers based on your proprietary knowledge base.
- Enabling AI assistants to retrieve specific help articles or feature guides.
- Reducing manual search time by asking natural language questions about your product.
常见问题
What are the prerequisites to use this server?
You need an Inkeep account (to manage and serve your RAG), the `uv` Python project manager, and Python. An API key must be generated from the Inkeep Dashboard.
How do I configure it with Claude Desktop?
Add a JSON entry to `claude_desktop_config.json` under `mcpServers`, specifying the `uv` command, the project directory, and environment variables including `INKEEP_API_BASE_URL`, `INKEEP_API_KEY`, and `INKEEP_MCP_TOOL_NAME`.
Where is my data stored and processed?
Your documentation is stored and indexed by Inkeep; the server only sends queries and retrieves results via Inkeep’s API. No local document storage is used.
What tool does the server expose and how should queries be framed?
The server exposes a single tool named `search-product-content`. Queries should be framed as conversational questions about the product content.
其他 分类下的更多 MCP 服务器
Klarix Intelligence Engine
KlarixB2B competitive intelligence, live sales battlecards, 5-axis ICP prospect fit scoring, and tech stack teardowns over MCP and REST with cited public-web evidence.
ICSS
chokcoco不止于 CSS
20.7K
Volley.sh
VolleyA good sequence diagram can solve almost any communication problem in engineering. Volley lets your agent write them as plain text, with the real request and response payloads on every arrow. It checks its own syntax wi
Maestro
mobile-dev-incPainless E2E Automation for Mobile and Web
14.8K
Awesome Mlops
visengerA curated list of references for MLOps
14.0K
评论