isaac-levine/forage
by Various
Self-improving tool discovery for AI agents. Agents find, install, and learn to use new MCP tools automatically.
MCP
isaac-levine/forage
Added 1 June 2026
Overview
A TypeScript project that enables AI agents to automatically discover, install, and learn to use new MCP tools. It aims to make tool discovery self-improving so agents can adapt their capabilities without manual intervention.
Best for
Best for
Developers building MCP-based AI agents that need dynamic tool discovery and integration
Use cases
- Enabling an agent to find and add relevant MCP tools on the fly
- Automating the installation of new tools during agent runtime
- Teaching agents how to use discovered tools without prior configuration
How to use
Install
npx forage-mcp init --client cursor Tools exposed
forage_searchforage_evaluateforage_installforage_learnforage_statusforage_uninstall
Tested with
Claude Code, Cursor
Notes
A TypeScript project that enables AI agents to automatically discover, install, and learn to use new MCP tools. It aims to make tool discovery self-improving so agents can adapt their capabilities without manual intervention.
10 stars on GitHub. Last updated 2026-02-21. Licensed MIT.
Use cases
- Enabling an agent to find and add relevant MCP tools on the fly
- Automating the installation of new tools during agent runtime
- Teaching agents how to use discovered tools without prior configuration
Pros
- Reduces manual setup for tool integration in agent workflows
- Self-improving mechanism allows agents to expand capabilities autonomously
- Open source and focused on MCP ecosystem
Cons
- Very small community (10 stars) suggests limited adoption and support
- Dependent on MCP standard adoption and tool availability
- Requires careful management of agent permissions for automatic installations
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Reduces manual setup for tool integration in agent workflows
- Self-improving mechanism allows agents to expand capabilities autonomously
- Open source and focused on MCP ecosystem
Cons
- Very small community (10 stars) suggests limited adoption and support
- Dependent on MCP standard adoption and tool availability
- Requires careful management of agent permissions for automatic installations
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