--- title: "agent-learning-kit vs mcp-agent" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/future-agi-agent-learning-kit-vs-lastmile-ai-mcp-agent" tools: ["future-agi-agent-learning-kit", "lastmile-ai-mcp-agent"] --- # agent-learning-kit vs mcp-agent *GraphCanon updated Sep 20, 2026* ## Verdict Pick agent-learning-kit if agent-learning-kit is a Python-based toolkit for evaluating and simulating AI workflows, particularly suited for AI agents. It offers optional extras for specific functionalities and a TypeScript SDK for broader language; pick mcp-agent if allows creation of efficient AI agents via Model Context Protocol with workflow patterns. [agent-learning-kit](https://futureagi.com) reports 119 GitHub stars, 44 forks, and 19 open issues, last pushed Sep 18, 2026. [mcp-agent](https://github.com/lastmile-ai/mcp-agent) has 8.5k stars, 891 forks, and 138 open issues, last pushed Jan 25, 2026. Figures are from public GitHub metadata via [agent-learning-kit's repository](https://github.com/future-agi/agent-learning-kit) and [mcp-agent's repository](https://github.com/lastmile-ai/mcp-agent). | | [agent-learning-kit](/tools/future-agi-agent-learning-kit.md) | [mcp-agent](/tools/lastmile-ai-mcp-agent.md) | | --- | --- | --- | | Tagline | General Purpose Evaluation and Simulation Environment for all your AI related Workflows | Build effective AI agents with Model Context Protocol. | | Stars | 119 | 8,549 | | Forks | 44 | 891 | | Open issues | 19 | 138 | | Language | Python | Python | | Adopt for | agent-learning-kit is a Python-based toolkit for evaluating and simulating AI workflows, particularly suited for AI agents. It offers optional extras for specific functionalities and a TypeScript SDK for broader language | Allows creation of efficient AI agents via Model Context Protocol with workflow patterns | | Persona | - | - | | Runtime | - | - | | License | Other | Apache-2.0 | | Categories | AI Agents, Evaluation & Observability | AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agent-learning-kit](/tools/future-agi-agent-learning-kit.md) | [mcp-agent](/tools/lastmile-ai-mcp-agent.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 237d | | Open issues (now) | 19 | 138 | | Stars delta | +1 (30d) | +71 (30d) | | Open issues delta | +13 (30d) | -2 (30d) | | Full report | [trust report](/tools/future-agi-agent-learning-kit/trust.md) | [trust report](/tools/lastmile-ai-mcp-agent/trust.md) | ## Shared compatibility - **Python**: [agent-learning-kit](/tools/future-agi-agent-learning-kit.md) - Python runtime; [mcp-agent](/tools/lastmile-ai-mcp-agent.md) - Python runtime ## Decision facts: agent-learning-kit - **Adopt for:** agent-learning-kit is a Python-based toolkit for evaluating and simulating AI workflows, particularly suited for AI agents. It offers optional extras for specific functionalities and a TypeScript SDK for broader language ## Decision facts: mcp-agent - **Adopt for:** Allows creation of efficient AI agents via Model Context Protocol with workflow patterns ## Choose when ### Choose agent-learning-kit if… - License: agent-learning-kit is Other, mcp-agent is Apache-2.0. - Tags unique to agent-learning-kit: agentic-ai, cicd, evaluation, ml. - Also covers Evaluation & Observability. - When you need a comprehensive environment for evaluating and simulating AI workflows, especially for AI agents ### Choose mcp-agent if… - License: mcp-agent is Apache-2.0, agent-learning-kit is Other. - Tags unique to mcp-agent: agents, llm, mcp, model-context-protocol. - Need to implement the Model Context Protocol specifically in your agent development ## When NOT to use agent-learning-kit - If your project strictly requires a different programming language other than Python or TypeScript - When you need a tool that is already at a mature v1 release, as agent-learning-kit is still developing its TypeScript SDK and extras ## When NOT to use mcp-agent - Require a more customizable approach beyond pre-defined protocol and workflows - Project demands specific AI frameworks unsupported by Model Context Protocol directly ## Common questions ### What is the difference between agent-learning-kit and mcp-agent? agent-learning-kit: General Purpose Evaluation and Simulation Environment for all your AI related Workflows. mcp-agent: Build effective AI agents with Model Context Protocol.. See the comparison table for live GitHub stats and shared categories. ### When should I choose agent-learning-kit over mcp-agent? Choose agent-learning-kit over mcp-agent when License: agent-learning-kit is Other, mcp-agent is Apache-2.0; Tags unique to agent-learning-kit: agentic-ai, cicd, evaluation, ml; Also covers Evaluation & Observability; When you need a comprehensive environment for evaluating and simulating AI workflows, especially for AI agents. ### When should I choose mcp-agent over agent-learning-kit? Choose mcp-agent over agent-learning-kit when License: mcp-agent is Apache-2.0, agent-learning-kit is Other; Tags unique to mcp-agent: agents, llm, mcp, model-context-protocol; Need to implement the Model Context Protocol specifically in your agent development. ### When should I avoid agent-learning-kit? If your project strictly requires a different programming language other than Python or TypeScript When you need a tool that is already at a mature v1 release, as agent-learning-kit is still developing its TypeScript SDK and extras ### When should I avoid mcp-agent? Require a more customizable approach beyond pre-defined protocol and workflows Project demands specific AI frameworks unsupported by Model Context Protocol directly ### Is agent-learning-kit or mcp-agent more popular on GitHub? mcp-agent has more GitHub stars (8,549 vs 119). Stars measure visibility, not whether either tool fits your constraints. ### Are agent-learning-kit and mcp-agent open source? Yes - both are open-source projects on GitHub (agent-learning-kit: Other, mcp-agent: Apache-2.0). ### Where can I find alternatives to agent-learning-kit or mcp-agent? GraphCanon lists graph-backed alternatives at [agent-learning-kit alternatives](/tools/future-agi-agent-learning-kit/alternatives) and [mcp-agent alternatives](/tools/lastmile-ai-mcp-agent/alternatives) ([agent-learning-kit markdown twin](/tools/future-agi-agent-learning-kit/alternatives.md), [mcp-agent markdown twin](/tools/lastmile-ai-mcp-agent/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/future-agi-agent-learning-kit-vs-lastmile-ai-mcp-agent.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agent-learning-kit or mcp-agent? agent-learning-kit: Very active. mcp-agent: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for agent-learning-kit and mcp-agent? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agent-learning-kit trust report](/tools/future-agi-agent-learning-kit/trust); [mcp-agent trust report](/tools/lastmile-ai-mcp-agent/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=future-agi-agent-learning-kit`](/api/graphcanon/graph?tool=future-agi-agent-learning-kit) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_