Teleport Documentation
Search and query Teleport's documentation using embeddings stored in a local Chroma vector database.
teleport-docs-mcp
Build a MCP server for Teleport Documentation
How it works
Embeddings generated from teleport docs are saved in a Chroma database. A MCP tool is provided to do the vector search and return the result from the database. Note that no LLM model is used to interpret the result within the MCP tool. It's up to the AI tool that calls the MCP tool to interpret the result.
Use from Dockerhub
https://hub.docker.com/r/stevetelelport/teleport-docs-mcp
stdio
docker run --rm -i stevetelelport/teleport-docs-mcp:v0.1.0
or in config json format:
{
"mcpServers": {
"teleport-docs": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"stevetelelport/teleport-docs-mcp:v0.1.0"
]
}
}
}
note that it takes a few seconds to spin up.
sse
docker run -d --name teleport-docs-mcp-sse -p 8282:8000 stevetelelport/teleport-docs-mcp:v0.1.0 uv run main.py --sse --host 0.0.0.0
Local Development
uv
Install uv:
curl -Ls https://astral.sh/uv/install.sh | sh
And install packages:
uv pip install -r requirement.txt
Build local docker
Build
$ docker build -t teleport-docs-mcp .
Stdio
$ docker run --rm -i teleport-docs-mcp
SSE
$ docker run --name teleport-docs-mcp-sse -d -p 8282:8000 teleport-docs uv main.py --sse --host 0.0.0.0
MCP config (stdio)
Replace with your directory path!
{
"mcpServers": {
"teleport-docs": {
"command": "uv",
"args": [
"--directory",
"/path/to/teleport-docs-mcp",
"run",
"main.py"
]
}
}
}
Rebuild database
The vector database is prepopulated and provided with this repo. You can refresh the data by removing existing indexes, and copy the latest pages from the teleport OSS GitHub repo.
To prep files:
rm -rf docs/pages
rm -rf docs/pages_fixed
cp /path/to/teleport/docs/pages docs/pages`
cp /path/to/teleport/examples docs/examples`
python3 fix_include.py
To generate new db:
rm -rf chroma_index/
python3 embed.py
It takes a while to generate though.
Related Servers
Weather
Provides weather data using the US National Weather Service (NWS) API. Built with pure JavaScript ES Modules.
eBird MCP Server
Query rich bird observation data from the eBird API using natural language.
GPT Researcher
Conducts autonomous, in-depth research by exploring and validating multiple sources to provide relevant and up-to-date information.
The Movie Database (TMDB)
Integrates with The Movie Database (TMDB) API, allowing AI assistants to search for movies, retrieve details, and generate related content.
ChunkHound
A local-first semantic code search tool with vector and regex capabilities, designed for AI assistants.
MarineTraffic MCP Server
Provides access to MarineTraffic vessel tracking data.
OpenAI WebSearch
Provides web search functionality for AI assistants using the OpenAI API, enabling access to up-to-date information.
Genji MCP Server
Search and analyze classical Japanese literature using the Genji API, with advanced normalization features.
Scholarly
Search for academic articles using scholarly vendors.
Web Search MCP
Scrapes Google search results using a headless browser. Requires Chrome to be installed.