Contextual Mcp Server
Wire your coding agent to Contextual AI RAG so answers pull from your indexed knowledge in single-agent or multi-agent setups.
Overview
Contextual MCP Server is a Build-phase MCP server that connects coding agents to Contextual AI RAG in single-agent or multi-agent mode over stdio.
What is this MCP server?
- RAG-enabled retrieval through Contextual AI exposed as MCP tools over stdio
- Single-agent mode (AGENT_ID set) and multi-agent mode (omit AGENT_ID)
- PyPI package contextual-mcp-server v0.1.0 with required API_KEY
- Published server schema 2025-09-29 for registry-compatible manifests
- Server version 0.1.0 on PyPI identifier contextual-mcp-server
- Transport: stdio; registry schema 2025-09-29
- Required env: API_KEY; optional AGENT_ID for single-agent mode only
What problem does it solve?
Agents hallucinate product facts when your real documentation lives outside the model context window.
Who is it for?
Indie builders shipping agent features who already use Contextual AI and want stdio MCP in Claude Code or Cursor.
Skip if: Teams that need zero cloud API keys, self-hosted embeddings only, or GitHub-wide repo browsing without a Contextual AI account.
What do I get? / Deliverables
After registration, the agent can query Contextual AI-backed retrieval so implementation answers cite your governed knowledge base.
- MCP tools that query Contextual AI RAG from your agent session
- Configurable single-agent (with AGENT_ID) or multi-agent routing
Recommended MCP Servers
Journey fit
Canonical shelf is Build because you register this MCP while wiring agent tooling and external AI services into the product stack. Integrations is where RAG-backed MCP servers land—stdio PyPI package plus API keys, not a standalone research-only bookmark.
How it compares
Managed RAG MCP bridge, not a public GitHub reader or a local provenance ledger.
Common Questions / FAQ
Who is contextual-mcp-server for?
Solo and small teams building with agent IDEs who want Contextual AI retrieval inside MCP tool calls.
When should I use contextual-mcp-server?
Use it during Build when you integrate external knowledge into the agent workflow and have a Contextual AI API key ready.
How do I add contextual-mcp-server to my agent?
Install the PyPI package contextual-mcp-server, configure stdio transport, set API_KEY, set AGENT_ID only for single-agent mode, then register the server in your MCP client.