trieve-mcp-server

📋 Overview:

The webpage is a directory view of the "mcp-server" folder within the "clients" directory of the "trieve" repository, owned by "devflowinc" on GitHub. Trieve is described as an all-in-one infrastructure for search, recommendations, RAG (Retrieval-Augmented Generation), and analytics offered via API. The "mcp-server" is a Model Context Protocol (MCP) server. The page provides access to the files and subdirectories within this folder, along with repository-level navigation and actions.

⭐ Key Points:
* The webpage displays the file structure of a specific directory within a GitHub repository.
* The repository, "trieve", offers infrastructure for search, recommendations, RAG, and analytics.
* The "mcp-server" directory contains code for a Model Context Protocol server.
* The site offers standard GitHub repository features, such as code browsing, issue tracking, and pull requests.

* The page includes a README.md file detailing the functionality, installation, configuration, and usage of the trieve-mcp-server.

🔍 Main Findings:
* The "trieve-mcp-server" facilitates interaction with the Trieve API through agentic tools.
* Installation can be done automatically via Smithery or manually using npm.
* Configuration requires setting environment variables for the Trieve API key and organization ID.
* The server exposes Trieve datasets as resources with a specific URI format.

* The MCP server supports integration with Claude Desktop.

📊 Details:
* The page provides links for signing in or signing up to GitHub.
* It lists the files and subdirectories within the "clients/mcp-server" path, including `src`, `.gitignore`, `Dockerfile`, `README.md`, `package.json`, `smithery.yaml`, `tsconfig.json`, and `vitest.config.ts`.
* The README.md details:
* Features: Semantic search, dataset information access, environment variable and CLI argument support, TypeScript implementation.
* Installation: Smithery (`npx -y @smithery/cli install trieve-mcp-server --client claude`) and npm (`npm install trieve-mcp-server`) methods.
* Configuration: `TRIEVEAPIKEY`, `TRIEVEORGANIZATIONID` (required), and `TRIEVEDATASETID` (optional) environment variables, and CLI arguments.
* Usage: Running the server (`trieve-mcp-server`), available tools ("search"), and resource URI format (`trieve://datasets/{dataset-id}`).
* Claude Desktop Integration: Specific configuration for `claudedesktopconfig.json`.

* Development: Setup instructions (clone, install dependencies, configure `.env`, build) and available scripts.

🎯 Conclusion:
The webpage serves as a code repository directory, providing access to the source code and documentation for the "trieve-mcp-server," a component designed to enable AI agents to interact with the Trieve API and datasets. The README provides detailed instructions for installation, configuration, and usage.