--- title: "ECC vs mcp-use" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/affaan-m-ecc-vs-mcp-use-mcp-use" tools: ["affaan-m-ecc", "mcp-use-mcp-use"] --- # ECC vs mcp-use *GraphCanon updated Jul 11, 2026* ## Verdict Pick ECC when eCC is primarily JavaScript; mcp-use is TypeScript; pick mcp-use when mcp-use is primarily TypeScript; ECC is JavaScript. [ECC](https://ecc.tools) reports 228k GitHub stars, 35k forks, and 93 open issues, last pushed Jul 9, 2026. [mcp-use](https://manufact.com) has 10k stars, 1.4k forks, and 103 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [ECC's repository](https://github.com/affaan-m/ECC) and [mcp-use's repository](https://github.com/mcp-use/mcp-use). | | [ECC](/tools/affaan-m-ecc.md) | [mcp-use](/tools/mcp-use-mcp-use.md) | | --- | --- | --- | | Tagline | The agent harness performance optimization system for AI agents | The fullstack MCP framework to develop MCP Apps for ChatGPT / Claude & MCP Servers for AI Agents. | | Stars | 228,395 | 10,281 | | Forks | 35,037 | 1,358 | | Open issues | 93 | 103 | | Language | JavaScript | TypeScript | | Adopt for | ECC is a performance optimization system for AI agents built to enhance skills, instincts, memory, security, and development processes. | - | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | AI Agents, Developer Tools | AI Agents, Developer Tools, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ECC](/tools/affaan-m-ecc.md) | [mcp-use](/tools/mcp-use-mcp-use.md) | | --- | --- | --- | | Days since push | 2d | 0d | | Open issues (now) | 93 | 103 | | Owner type | User | Organization | | Full report | [trust report](/tools/affaan-m-ecc/trust.md) | [trust report](/tools/mcp-use-mcp-use/trust.md) | ## Decision facts: ECC - **Hosting:** unknown - ECC requires JavaScript environment and is open-source, licensed under MIT. Specific setup details are not provided within repository data. - **Pricing:** freemium - Being open source with an MIT license, ECC itself is free to use, but additional features or support might incur costs outside of the core project. - **Adopt for:** ECC is a performance optimization system for AI agents built to enhance skills, instincts, memory, security, and development processes. ## Choose when ### Choose ECC if… - ECC is primarily JavaScript; mcp-use is TypeScript. - ECC requires JavaScript environment and is open-source, licensed under MIT. Specific setup details are not provided within repository data. - Pricing: Being open source with an MIT license, ECC itself is free to use, but additional features or support might incur costs outside of the core project.. - Tags unique to ECC: ai-agents, anthropic, claude, llm. - When you are specifically working with AI agents like Claude Code and Codex that require advanced performance tuning across multiple dimensions such as skills and memory management. ### Choose mcp-use if… - mcp-use is primarily TypeScript; ECC is JavaScript. - Tags unique to mcp-use: agentic-framework, ai, apps-sdk, chatgpt. - Also covers LLM Frameworks. ## When NOT to use ECC - For projects focusing solely on traditional software development workflows without AI components, ECC's specialized tools are not necessary. - In scenarios where you're working with closed-source or proprietary AI systems that do not allow for the same levels of customization as open platforms like those optimized by ECC. ## When NOT to use mcp-use - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between ECC and mcp-use? ECC: The agent harness performance optimization system for AI agents. mcp-use: The fullstack MCP framework to develop MCP Apps for ChatGPT / Claude & MCP Servers for AI Agents.. See the comparison table for live GitHub stats and shared categories. ### When should I choose ECC over mcp-use? Choose ECC over mcp-use when ECC is primarily JavaScript; mcp-use is TypeScript; ECC requires JavaScript environment and is open-source, licensed under MIT. Specific setup details are not provided within repository data; Pricing: Being open source with an MIT license, ECC itself is free to use, but additional features or support might incur costs outside of the core project.; Tags unique to ECC: ai-agents, anthropic, claude, llm; When you are specifically working with AI agents like Claude Code and Codex that require advanced performance tuning across multiple dimensions such as skills and memory management. ### When should I choose mcp-use over ECC? Choose mcp-use over ECC when mcp-use is primarily TypeScript; ECC is JavaScript; Tags unique to mcp-use: agentic-framework, ai, apps-sdk, chatgpt; Also covers LLM Frameworks. ### When should I avoid ECC? For projects focusing solely on traditional software development workflows without AI components, ECC's specialized tools are not necessary. In scenarios where you're working with closed-source or proprietary AI systems that do not allow for the same levels of customization as open platforms like those optimized by ECC. ### When should I avoid mcp-use? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is ECC or mcp-use more popular on GitHub? ECC has more GitHub stars (228,395 vs 10,281). Stars measure visibility, not whether either tool fits your constraints. ### Are ECC and mcp-use open source? Yes - both are open-source projects on GitHub (ECC: MIT, mcp-use: MIT). ### Where can I find alternatives to ECC or mcp-use? GraphCanon lists graph-backed alternatives at [ECC alternatives](/tools/affaan-m-ecc/alternatives) and [mcp-use alternatives](/tools/mcp-use-mcp-use/alternatives) ([ECC markdown twin](/tools/affaan-m-ecc/alternatives.md), [mcp-use markdown twin](/tools/mcp-use-mcp-use/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/affaan-m-ecc-vs-mcp-use-mcp-use.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ECC or mcp-use? ECC: Very active. mcp-use: Very active. 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 ECC and mcp-use? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ECC trust report](/tools/affaan-m-ecc/trust); [mcp-use trust report](/tools/mcp-use-mcp-use/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=affaan-m-ecc`](/api/graphcanon/graph?tool=affaan-m-ecc) - 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/_