{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/10"}],"enrichment":{"capability":"Exposes LangSmith observability data (conversation history, prompts, runs, datasets, experiments, billing) through a Model Context Protocol server that language models can query.","skillfed_tags":["mcp-server","langsmith-integration","llm-observability"],"use_cases":["Query conversation history from LangSmith threads within an MCP client to provide context to language models.","Retrieve and manage prompts stored in LangSmith workspaces programmatically through MCP tool calls.","Fetch execution traces and runs from LangSmith projects to analyze LLM application behavior in real time.","List and read datasets and examples from LangSmith for evaluation and testing workflows.","Access experiment results and metrics (latency, cost, feedback) for dataset-based evaluations.","Monitor organization billing usage and trace counts across workspaces via MCP queries."],"what_it_does":"This package implements a Model Context Protocol (MCP) server that bridges language models to LangSmith, an observability platform for LLM applications. It exposes tools for querying conversation threads, managing prompts, fetching execution traces and runs, accessing datasets and experiments, and retrieving billing metrics\u2014all through a standardized MCP interface that LLM clients can call. The server can run locally (via PyPI or from source) or be accessed as a hosted HTTP endpoint without local installation.\n\nThe package depends on fastmcp, langsmith, langchain-core, and uvicorn to handle MCP protocol transport, LangSmith API communication, and async HTTP serving. It requires Python 3.11 or later. While the repository is archived and no longer actively maintained, the package remains functional for integrating LangSmith data into MCP-compatible clients like Cursor or Claude Desktop.","worth_installing":"Yes, if you actively use LangSmith and need MCP integration. The package is low-friction to install and permissively licensed. However, the archived repository and abandoned maintenance status mean no active bug fixes or feature development\u2014use it for stable, read-heavy workflows (querying history, datasets, runs) rather than as a foundation for custom extensions. If you need a hosted solution, the Render instance is available but its long-term availability is not guaranteed."},"id":"langsmith-mcp-server","links":{"html":"https://skillfed.io/packages/langsmith-mcp-server","md":"https://skillfed.io/packages/langsmith-mcp-server.md","pypi":"https://pypi.org/project/langsmith-mcp-server/"},"maintenance":{"status":"abandoned"},"meta":{"latest_release":"2026-02-25","license_spdx":"MIT","license_treatment":"permissive","name":"langsmith-mcp-server","python_support":"supports_current","summary":"MCP server for Langsmith SDK integration"},"popularity":{"monthly_downloads":108107,"position":12578,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.1.1"}