--- title: "awesome vs awesome-mcp-servers" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/sindresorhus-awesome-vs-tensorblock-awesome-mcp-servers" tools: ["sindresorhus-awesome", "tensorblock-awesome-mcp-servers"] --- # awesome vs awesome-mcp-servers *GraphCanon updated Aug 4, 2026* ## Verdict Pick awesome if a curated collection of resources on a variety of technological topics, emphasizing hardware and robotics; pick awesome-mcp-servers if decision Facts for awesome-mcp-servers. [awesome](https://github.com/sindresorhus/awesome) reports 492k GitHub stars, 36k forks, and 100 open issues, last pushed Jun 30, 2026. [awesome-mcp-servers](https://tensorblock.co) has 790 stars, 638 forks, and 36 open issues, last pushed Jul 27, 2026. Figures are from public GitHub metadata via [awesome's repository](https://github.com/sindresorhus/awesome) and [awesome-mcp-servers's repository](https://github.com/TensorBlock/awesome-mcp-servers). | | [awesome](/tools/sindresorhus-awesome.md) | [awesome-mcp-servers](/tools/tensorblock-awesome-mcp-servers.md) | | --- | --- | --- | | Tagline | 😎 Awesome lists about all kinds of interesting topics | A comprehensive collection of Model Context Protocol (MCP) servers | | Stars | 492,352 | 790 | | Forks | 36,224 | 638 | | Open issues | 100 | 36 | | Language | - | TypeScript | | Adopt for | A curated collection of resources on a variety of technological topics, emphasizing hardware and robotics. | Decision Facts for awesome-mcp-servers | | Persona | - | - | | Runtime | - | - | | License | CC0-1.0 | MIT | | Categories | Developer Tools | Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome](/tools/sindresorhus-awesome.md) | [awesome-mcp-servers](/tools/tensorblock-awesome-mcp-servers.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 34d | 0d | | Open issues (now) | 100 | 36 | | Owner type | User | Organization | | Full report | [trust report](/tools/sindresorhus-awesome/trust.md) | [trust report](/tools/tensorblock-awesome-mcp-servers/trust.md) | ## Decision facts: awesome - **Adopt for:** A curated collection of resources on a variety of technological topics, emphasizing hardware and robotics. ## Decision facts: awesome-mcp-servers - **Adopt for:** Decision Facts for awesome-mcp-servers ## Choose when ### Choose awesome if… - License: awesome is CC0-1.0, awesome-mcp-servers is MIT. - Tags unique to awesome: awesome, awesome-list, lists, resources. - Also covers Developer Tools. - When you need well-organized access to diverse technical subjects from IoT to robotics ### Choose awesome-mcp-servers if… - License: awesome-mcp-servers is MIT, awesome is CC0-1.0. - Tags unique to awesome-mcp-servers: anthropic, genai, mcp, mcp-server. - Also covers Model Training. - awesome-mcp-servers ships an MCP server manifest. - Need TypeScript-based MCP server implementations and resources. ## When NOT to use awesome - If seeking specific coding frameworks or libraries for software development rather than hardware-focused resources - In scenarios requiring real-time interactive support or forums, as the content is static lists without active discussion ## When NOT to use awesome-mcp-servers - Require backend languages other than TypeScript for MCP servers. - Looking for a general-purpose AI development toolkit, not MCP-specific solutions. ## Common questions ### What is the difference between awesome and awesome-mcp-servers? awesome: 😎 Awesome lists about all kinds of interesting topics. awesome-mcp-servers: A comprehensive collection of Model Context Protocol (MCP) servers. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome over awesome-mcp-servers? Choose awesome over awesome-mcp-servers when License: awesome is CC0-1.0, awesome-mcp-servers is MIT; Tags unique to awesome: awesome, awesome-list, lists, resources; Also covers Developer Tools; When you need well-organized access to diverse technical subjects from IoT to robotics. ### When should I choose awesome-mcp-servers over awesome? Choose awesome-mcp-servers over awesome when License: awesome-mcp-servers is MIT, awesome is CC0-1.0; Tags unique to awesome-mcp-servers: anthropic, genai, mcp, mcp-server; Also covers Model Training; awesome-mcp-servers ships an MCP server manifest; Need TypeScript-based MCP server implementations and resources. ### When should I avoid awesome? If seeking specific coding frameworks or libraries for software development rather than hardware-focused resources In scenarios requiring real-time interactive support or forums, as the content is static lists without active discussion ### When should I avoid awesome-mcp-servers? Require backend languages other than TypeScript for MCP servers. Looking for a general-purpose AI development toolkit, not MCP-specific solutions. ### Is awesome or awesome-mcp-servers more popular on GitHub? awesome has more GitHub stars (492,352 vs 790). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome and awesome-mcp-servers open source? Yes - both are open-source projects on GitHub (awesome: CC0-1.0, awesome-mcp-servers: MIT). ### Where can I find alternatives to awesome or awesome-mcp-servers? GraphCanon lists graph-backed alternatives at [awesome alternatives](/tools/sindresorhus-awesome/alternatives) and [awesome-mcp-servers alternatives](/tools/tensorblock-awesome-mcp-servers/alternatives) ([awesome markdown twin](/tools/sindresorhus-awesome/alternatives.md), [awesome-mcp-servers markdown twin](/tools/tensorblock-awesome-mcp-servers/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/sindresorhus-awesome-vs-tensorblock-awesome-mcp-servers.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome or awesome-mcp-servers? awesome: Steady. awesome-mcp-servers: 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 awesome and awesome-mcp-servers? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome trust report](/tools/sindresorhus-awesome/trust); [awesome-mcp-servers trust report](/tools/tensorblock-awesome-mcp-servers/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=sindresorhus-awesome`](/api/graphcanon/graph?tool=sindresorhus-awesome) - 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/_