Conduit
A local-first MCP gateway that reduces token usage by ~90% by exposing 3 meta-tools instead of hundreds, working across all major AI clients.
Conduit
What is Conduit?
Conduit vs Similar AI Tools
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How to use Conduit?
- 1Download and install Conduit from GitHub releases.
- 2Add your MCP servers in the Conduit app.
- 3Authenticate each server once (keys stored in OS keychain).
- 4Point your AI client (Claude, Cursor, VS Code, etc.) to Conduit's local endpoint.
- 5Use the client as usual; Conduit handles tool selection in the background.
Conduit Key Features
- Reduces token overhead by ~90% via 3 meta-tools
- Works with Claude, Cursor, VS Code, Windsurf, Codex, and more
- Local-first with secrets in OS keychain
- Per-tool governance to enable/disable any tool across all clients
- Live observability with per-server latency, errors, and audit trail
- No Docker or cloud required; runs as a native desktop app
Conduit Use Cases
- Optimizing AI agent performance when using many MCP servers
- Centralizing MCP server management for a team of developers
- Reducing API costs by minimizing token usage
- Enhancing security by keeping API keys out of client configs
Conduit Pricing & Free Credits
Conduit currently operates on a Free model.
This tool is completely free to use
Conduit Pros & Cons
Pros
- Dramatically reduces token usage (up to ~90%)
- Works with multiple AI clients without reconfiguration
- Local-first architecture ensures data privacy
- API keys stored securely in OS keychain
- Granular tool governance for safety
- Built-in observability tools
Cons
- Requires initial setup and server configuration
- Limited to MCP-compatible servers and clients
- May not be suitable for non-developer users
What is Conduit best for?
- Developers using AI coding assistants like Claude, Cursor, or Codex
- Teams managing multiple MCP servers across different tools
- Users looking to reduce token costs and improve agent speed
Conduit FAQ
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