--- title: "awesome-mcp-servers vs doit" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/punkpeye-awesome-mcp-servers-vs-pydoit-doit" tools: ["punkpeye-awesome-mcp-servers", "pydoit-doit"] --- # awesome-mcp-servers vs doit *GraphCanon updated Jul 15, 2026* ## Verdict Pick awesome-mcp-servers when tags unique to awesome-mcp-servers: ai, mcp, server-resources; pick doit when tags unique to doit: build-automation, build-system, build-tool, cli. [awesome-mcp-servers](https://glama.ai/mcp/servers) reports 91k GitHub stars, 13k forks, and 2.6k open issues, last pushed Jul 4, 2026. [doit](http://pydoit.org) has 2.1k stars, 192 forks, and 93 open issues, last pushed Feb 12, 2026. Figures are from public GitHub metadata via [awesome-mcp-servers's repository](https://github.com/punkpeye/awesome-mcp-servers) and [doit's repository](https://github.com/pydoit/doit). | | [awesome-mcp-servers](/tools/punkpeye-awesome-mcp-servers.md) | [doit](/tools/pydoit-doit.md) | | --- | --- | --- | | Tagline | A collection of MCP servers | CLI task management & automation tool | | Stars | 90,602 | 2,073 | | Forks | 12,821 | 192 | | Open issues | 2,557 | 93 | | Language | - | Python | | Adopt for | awesome-mcp-servers is a collection focused specifically on MCP servers with an emphasis on AI integration. | - | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Developer Tools | Computer Vision, Data & Retrieval, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-mcp-servers](/tools/punkpeye-awesome-mcp-servers.md) | [doit](/tools/pydoit-doit.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 6d | 152d | | Open issues (now) | 2.6k | 93 | | Owner type | User | Organization | | Full report | [trust report](/tools/punkpeye-awesome-mcp-servers/trust.md) | [trust report](/tools/pydoit-doit/trust.md) | ## Decision facts: awesome-mcp-servers - **Adopt for:** awesome-mcp-servers is a collection focused specifically on MCP servers with an emphasis on AI integration. ## Choose when ### Choose awesome-mcp-servers if… - Tags unique to awesome-mcp-servers: ai, mcp, server-resources. - If your project requires detailed resources and tools around MCP server capabilities for AI projects, awesome-mcp-servers is well-suited as it focuses solely on this niche area of technology. - More GitHub stars (91k vs 2.1k) - visibility, not fit. ### Choose doit if… - Tags unique to doit: build-automation, build-system, build-tool, cli. - Also covers Computer Vision, Data & Retrieval. - Leaner open-issue backlog (93). ## When NOT to use awesome-mcp-servers - Avoid using awesome-mcp-servers if your project does not involve utilizing or exploring the specific functionalities of MCP servers in relation to AI applications. ## When NOT to use doit - Last GitHub push was 153 days ago (slowing maintenance, Feb 12, 2026). Validate activity before betting a new project on doit. - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. ## Common questions ### What is the difference between awesome-mcp-servers and doit? awesome-mcp-servers: A collection of MCP servers. doit: CLI task management & automation tool. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-mcp-servers over doit? Choose awesome-mcp-servers over doit when Tags unique to awesome-mcp-servers: ai, mcp, server-resources; If your project requires detailed resources and tools around MCP server capabilities for AI projects, awesome-mcp-servers is well-suited as it focuses solely on this niche area of technology; More GitHub stars (91k vs 2.1k) - visibility, not fit. ### When should I choose doit over awesome-mcp-servers? Choose doit over awesome-mcp-servers when Tags unique to doit: build-automation, build-system, build-tool, cli; Also covers Computer Vision, Data & Retrieval; Leaner open-issue backlog (93). ### When should I avoid awesome-mcp-servers? Avoid using awesome-mcp-servers if your project does not involve utilizing or exploring the specific functionalities of MCP servers in relation to AI applications. ### When should I avoid doit? Last GitHub push was 153 days ago (slowing maintenance, Feb 12, 2026). Validate activity before betting a new project on doit. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. ### Is awesome-mcp-servers or doit more popular on GitHub? awesome-mcp-servers has more GitHub stars (90,602 vs 2,073). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-mcp-servers and doit open source? Yes - both are open-source projects on GitHub (awesome-mcp-servers: MIT, doit: MIT). ### Where can I find alternatives to awesome-mcp-servers or doit? GraphCanon lists graph-backed alternatives at [awesome-mcp-servers alternatives](/tools/punkpeye-awesome-mcp-servers/alternatives) and [doit alternatives](/tools/pydoit-doit/alternatives) ([awesome-mcp-servers markdown twin](/tools/punkpeye-awesome-mcp-servers/alternatives.md), [doit markdown twin](/tools/pydoit-doit/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/punkpeye-awesome-mcp-servers-vs-pydoit-doit.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome-mcp-servers or doit? awesome-mcp-servers: Very active. doit: 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 awesome-mcp-servers and doit? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-mcp-servers trust report](/tools/punkpeye-awesome-mcp-servers/trust); [doit trust report](/tools/pydoit-doit/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=punkpeye-awesome-mcp-servers`](/api/graphcanon/graph?tool=punkpeye-awesome-mcp-servers) - 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/_