mcpbeat

Context Lens MCP Server

io.github.cornelcroi/context-lens
local only

Context Lens runs on your own machine — the client starts it, so there is no endpoint to ping. 209 installs a week from pypi.

Semantic search knowledge base with serverless LanceDB. Zero setup, 100% local, 25+ file types

Installs per day peak 74 · avg 36 · -31% w/w
a month agotoday
209
Installs / week
pypi · context-lens
Stars
on GitHub
Last commit
0 releases in 90 days
License
language unknown

Connect this server

This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.

run in your terminal
claude mcp add context-lens -- uvx context-lens
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "context-lens": {
      "args": [
        "context-lens"
      ],
      "command": "uvx"
    }
  }
}
~/.codex/config.toml
[mcp_servers.context-lens]
command = "uvx"
args = ["context-lens"]
.cursor/mcp.json
{
  "mcpServers": {
    "context-lens": {
      "args": [
        "context-lens"
      ],
      "command": "uvx"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "context-lens": {
      "args": [
        "context-lens"
      ],
      "command": "uvx"
    }
  }
}

Context Lens — questions

Answers built from our own checks of this server.

Why is there no uptime for Context Lens?
Context Lens runs on your own machine over stdio — there is no network address to reach, so uptime cannot be measured for it by anyone. What can be measured is adoption: the pypi package context-lens was installed 209 times last week.
How do I connect Context Lens?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It runs locally, so the command pulls context-lens straight from pypi; nothing to host, nothing to sign up for.
How many people use Context Lens?
The pypi package context-lens was installed 209 times in the last week. Week over week that is -31%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.