How do I install semantic-search-mcp-server?
Run `npm install` to install dependencies, then `npm run build` to compile the TypeScript project.
@jingchun19
Basic information
No overview available yet
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"semantic-search-mcp-server": {
"command": "node",
"args": [
"/absolute/path/to/semantic-search-mcp-server/dist/index.js"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
A Model Context Protocol (MCP) server built with mcp-framework for enhancing Claude Desktop with semantic search capabilities. It provides a structured way to develop and integrate custom MCP tools.
Install dependencies with npm install, build the project with npm run build, then add the server to your Claude Desktop configuration (either local development path or published npm package). The server automatically loads all tools defined in src/tools/ on startup.
mcp add tool <name>)Run `npm install` to install dependencies, then `npm run build` to compile the TypeScript project.
Add the server to your Claude Desktop config file (`claude_desktop_config.json`) with the appropriate command and args. For local development use `node` and the absolute path to `dist/index.js`; after publishing use `npx` with the package name.
Use the CLI command `mcp add tool my-tool` from the project root, or manually create a new tool in `src/tools/` following the example template.
Update `package.json` with a unique name, version, and other metadata, build the project, then run `npm login` and `npm publish`.
The server requires Node.js and npm. It is built on mcp-framework and uses TypeScript.
Shared, serverless, conflict-free memory for AI agents: a multi-machine drop-in for the MCP memory knowledge graph.

Search published GPU deployment, rack integration and structured cabling resources; read canonical documents and Leviathan Systems company service scope. Anonymous, read-only Streamable HTTP MCP. No credentials required.

Personal context for every AI: search, read, and write back to your private Markdown library of articles, threads, PDFs, notes, and captured ChatGPT/Claude/Gemini/Grok conversations. Remote server, OAuth 2.1 paste-and-au

One permissioned folder your team and your AI agents both log into.

Local AI agent for your Mac with a built-in MCP server: 18 tools for your notes and PDFs, a temporal memory graph, an on-device LLM and a neural voice. No account, no telemetry. No data centers required.
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