An MCP transport for pipecat. One MCP client holds one text conversation with one bot.
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Agents can do it too: POST https://wellknown.network/api/v1/claims with {"agent":"pipecat-mcp-transport","method":"well_known_file"} — machine-readable steps at claim.json, guide at /docs/claim.
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<div align="center"> <a href="https://github.com/pipecat-ai/pipecat"> <img alt="Pipecat" width="220px" height="auto" src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/pipecat.png"> </a> <p><em>A <a href="https://docs.pipecat.ai/api-reference/server/services/transport/mcp">community integration</a> for <a href="https://github.com/pipecat-ai/pipecat">Pipecat</a></em></p> </div> # pipecat-mcp-transport [](https://pypi.org/project/pipecat-mcp-transport) [](https://pypi.org/project/pipecat-mcp-transport) [](https://github.com/softcery/pipecat-mcp-transport/actions/workflows/check.yml) [](https://github.com/softcery/pipecat-mcp-transport/blob/main/LICENSE) An MCP transport for [pipecat](https://github.com/pipecat-ai/pipecat). It serves your pipecat bot as an MCP server, so any agent with an MCP client, for example Claude Code, talks to the bot. The bot keeps its pipeline, its tools and its history. The server exposes 2 tools, `start` and `chat`, over streamable HTTP. Tested with pipecat 1.14.0 and mcp 2.3.0 on Python 3.12, 3.13 and 3.14. ## Install ``` pip install pipecat-mcp-transport ``` ## Use `McpBotServer` serves your bot function. The bot reads its transport from the runner arguments, and that branch is the only edit an existing bot needs. ```python from pipecat.runner.types import RunnerArguments from pipecat.runner.utils import create_transport from pipecat.transports.base_transport import TransportParams from pipecat_mcp_transport import McpBotServer, McpRunnerArguments voice_params = TransportParams(audio_in_enabled=True,…
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