logrocket-mcp-replay

# LogRocket MCP Replay Records the requests your MCP server handles as LogRocket sessions so you can see how users' agents interact with your product: which tools they call and with what arguments, which resources and prompts they fetch, what they got back, and where errors happen. Works with MCP servers built on the official [`mcp`](https://pypi.org/project/mcp/) SDK, both 2.x (`MCPServer`, low-level `Server`) and 1.x (`FastMCP`, low-level `Server`), and on the standalone [`fastmcp`](https://pypi.org/project/fastmcp/) package (2.x, 3.x, 4.x), over any transport (stdio, SSE, Streamable HTTP). ## Installation ```bash uv add logrocket-mcp-replay # or: pip install logrocket-mcp-replay ``` ## Usage ```python import os from logrocket_mcp_replay import instrument server = build_my_mcp_server() instrument( server, api_key=os.environ["LOGROCKET_INGEST_KEY"], get_user=lambda ctx: {"id": ctx.request.headers["x-user-id"]} if ctx.request else None, ) ``` `instrument` records every request the server handles - tool calls, resource reads, prompt gets, listings, and any handler registered afterwards - and uploads batched request events to LogRocket from a background thread. Errors raised by handlers will be surfaced as LogRocket issues. ### API key Create an API key for your app in the LogRocket dashboard and pass it as `api_key`. The key both authenticates uploads and determines which LogRocket app sessions are recorded to. There is no separate appID to configure. ### Short-lived processes Events are buffered and flushed when the buffer fills, on a timer, and at interpreter exit. On platforms that freeze the process as soon as a response is sent (e.g., AWS Lambda), pass a `recorder` and flush it before returning: ```python from logrocket_mcp_replay import InstrumentOptions, RecorderOptions, create_recorder, instrument recorder = create_recorder(RecorderOptions(api_key=os.environ["LOGROCKET_INGEST_KEY"])) instrument(server, InstrumentOptions(api_key=os…