Contextual MCP Server runs on your own machine — the client starts it, so there is no endpoint to ping. 73 installs a week from pypi. Last commit 18 Sep 2025.
RAG-enabled MCP server using Contextual AI. Supports single-agent and multi-agent modes.
No commits for 12 months.
We read the source, 21 h ago · rules 3dff92dd89df
What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.
file_path = os.path.join(output_dir, filename)
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.
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.
claude mcp add contextual-mcp-server -- uvx contextual-mcp-server
{
"mcpServers": {
"contextual-mcp-server": {
"args": [
"contextual-mcp-server"
],
"command": "uvx"
}
}
}
[mcp_servers.contextual-mcp-server]
command = "uvx"
args = ["contextual-mcp-server"]
{
"mcpServers": {
"contextual-mcp-server": {
"args": [
"contextual-mcp-server"
],
"command": "uvx"
}
}
}
{
"mcpServers": {
"contextual-mcp-server": {
"args": [
"contextual-mcp-server"
],
"command": "uvx"
}
}
}
This one needs environment variables set before it will start:
API_KEY (Your Contextual AI API key), AGENT_ID (Your Contextual AI agent ID (required only for single-agent mode; omit for multi-agent mode)).
The author declared them in the registry entry; get the values from the project itself.
MCP RAG server with hybrid search, multi-KB support, and AI-powered chunk contextualization.
Local multi-client RAG server over the Model Context Protocol.
Hybrid vector + reasoning retrieval, agent memory, multi-agent orchestration, MCP server, and RAG.
Productivity-boosting RAG engine for codebases with multi-provider AI support and semantic search.
AI-powered vector knowledge graph MCP server for agents. Supports add node, add edge, semantic node
Local RAG MCP server with hybrid search, PDF/DOCX support, and zero-config setup
Local-first RAG engine with MCP server for AI agent integration.
Local-first memory for coding agents — MCP server, single SQLite file, local embeddings
Answers built from our own checks of this server.