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‎.gitignore‎

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*.sage.py
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# Environments
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.env
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.env*
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.venv
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env/
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venv/

‎.python-version‎

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3.10

‎README.md‎

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# mcp-server-python
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Inkeep MCP Server
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Inkeep MCP Server for your docs!
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### Dependencies
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- An account on [Inkeep](https://inkeep.com)
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- [`uv`](https://github.com/astral-sh/uv)
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### Setup
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```
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git clone [email protected]:inkeep/mcp-server-python.git
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cd mcp-server-python
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uv venv
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uv pip install -r pyproject.toml
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```
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You'll need these environment variables:
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```
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INKEEP_API_BASE_URL=https://api.inkeep.com/v1
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INKEEP_API_KEY=
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INKEEP_API_MODEL=inkeep-rag-20250310
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```
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To get an API key, go to the Inkeep Portal and create an API Integration.
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### `claude_desktop_config.json`
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```
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{
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"mcpServers": {
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"your-docs-by-inkeep-mcp-server": {
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"command": "uv",
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"args": [
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"--directory",
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"/ABSOLUTE/PATH/TO/PARENT/FOLDER/mcp-server-python",
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"run",
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"-m",
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"inkeep_mcp_server"
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],
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"env": {
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"INKEEP_API_BASE_URL": "https://api.inkeep.com/v1",
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"INKEEP_API_KEY": "YOUR_INKEEP_API_KEY",
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"INKEEP_API_MODEL": "inkeep-rag-20250310"
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}
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},
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}
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}
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```
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You may need to put the full path to the `uv` executable in the command field. You can get this by running `which uv` on MacOS/Linux or `where uv` on Windows.

‎inkeep_mcp_server/__main__.py‎

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from inkeep_mcp_server.server import mcp
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if __name__ == "__main__":
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mcp.run(transport="stdio")

‎inkeep_mcp_server/server.py‎

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import typing as T
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import openai
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from mcp.server.fastmcp import FastMCP
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from pydantic import BaseModel
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from inkeep_mcp_server.settings import inkeep_settings
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# Initialize FastMCP server
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mcp = FastMCP("inkeep-mcp-server")
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# https://docs.anthropic.com/en/docs/build-with-claude/citations#plain-text-documents
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class InkeepRAGDocument(BaseModel):
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# anthropic fields citation types
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type: str
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source: T.Dict
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title: T.Optional[str] = None
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context: T.Optional[str] = None
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# inkeep specific fields
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source_type: T.Optional[str] = None
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url: T.Optional[str] = None
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class InkeepRAGResponse(BaseModel):
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content: T.List[InkeepRAGDocument] = []
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async def make_inkeep_rag_request(query: str) -> InkeepRAGResponse:
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async with openai.AsyncOpenAI(
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base_url=inkeep_settings.INKEEP_API_BASE_URL,
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api_key=inkeep_settings.INKEEP_API_KEY,
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) as openai_client:
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# https://platform.openai.com/docs/guides/structured-outputs?api-mode=chat
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inkeep_rag_response = await openai_client.beta.chat.completions.parse(
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model=inkeep_settings.INKEEP_API_MODEL,
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messages=[
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{"role": "user", "content": query},
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],
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response_format=InkeepRAGResponse,
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)
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inkeep_rag_response_parsed = inkeep_rag_response.choices[0].message.parsed
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if inkeep_rag_response_parsed:
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return inkeep_rag_response_parsed
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else:
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return InkeepRAGResponse()
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@mcp.tool(
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name="rag-search",
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description="Search for relevant docs for a query using Inkeep's RAG API.",
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)
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async def rag_search(query: str) -> InkeepRAGResponse:
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return await make_inkeep_rag_request(query)

‎inkeep_mcp_server/settings.py‎

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from pydantic_settings import BaseSettings, SettingsConfigDict
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class InkeepSettings(BaseSettings):
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INKEEP_API_BASE_URL: str
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INKEEP_API_KEY: str
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INKEEP_API_MODEL: str
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model_config = SettingsConfigDict()
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inkeep_settings = InkeepSettings() # type: ignore

‎pyproject.toml‎

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[project]
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name = "inkeep-mcp-server"
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version = "0.1.0"
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description = "Inkeep MCP Server"
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readme = "README.md"
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requires-python = ">=3.10"
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dependencies = [
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"mcp[cli]>=1.3.0",
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"openai>=1.66.3",
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"pydantic-settings>=2.8.1",
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]
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[dependency-groups]
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dev = [
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"black>=25.1.0",
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"ipython>=8.34.0",
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"isort>=6.0.1",
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]

‎uv.lock‎

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