--- title: "awesome-mcp-servers vs awesome-mcp-servers" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/appcypher-awesome-mcp-servers-vs-tensorblock-awesome-mcp-servers" tools: ["appcypher-awesome-mcp-servers", "tensorblock-awesome-mcp-servers"] --- # awesome-mcp-servers vs awesome-mcp-servers *GraphCanon updated Aug 26, 2026* ## Verdict Pick awesome-mcp-servers if awesome-mcp-servers is a curated list of Model Context Protocol servers for AI applications, useful when you need specific resources related to MCP and less suitable if your focus is on other protocols; pick awesome-mcp-servers if decision Facts for awesome-mcp-servers. [awesome-mcp-servers](https://github.com/appcypher/awesome-mcp-servers) reports 5.8k GitHub stars, 2.2k forks, and 526 open issues, last pushed May 6, 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-mcp-servers's repository](https://github.com/appcypher/awesome-mcp-servers) and [awesome-mcp-servers's repository](https://github.com/TensorBlock/awesome-mcp-servers). | | [awesome-mcp-servers](/tools/appcypher-awesome-mcp-servers.md) | [awesome-mcp-servers](/tools/tensorblock-awesome-mcp-servers.md) | | --- | --- | --- | | Tagline | A curated list of Model Context Protocol servers | A comprehensive collection of Model Context Protocol (MCP) servers | | Stars | 5,757 | 790 | | Forks | 2,238 | 638 | | Open issues | 526 | 36 | | Language | - | TypeScript | | Adopt for | awesome-mcp-servers is a curated list of Model Context Protocol servers for AI applications, useful when you need specific resources related to MCP and less suitable if your focus is on other protocols. | Decision Facts for awesome-mcp-servers | | Persona | - | - | | Runtime | - | - | | License | - | MIT | | Categories | Model Training | Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-mcp-servers](/tools/appcypher-awesome-mcp-servers.md) | [awesome-mcp-servers](/tools/tensorblock-awesome-mcp-servers.md) | | --- | --- | --- | | Maintenance | Archived (8%) | Very active (96%) | | Days since push | 111d | 0d | | Archived on GitHub | Yes | No | | Open issues (now) | 526 | 36 | | Stars delta | +41 (30d) | Unknown | | Open issues delta | -8 (30d) | Unknown | | Owner type | User | Organization | | Full report | [trust report](/tools/appcypher-awesome-mcp-servers/trust.md) | [trust report](/tools/tensorblock-awesome-mcp-servers/trust.md) | ## Decision facts: awesome-mcp-servers - **Pricing:** unknown - The pricing model is unknown since the information provided does not specify any costs associated with using awesome-mcp-servers. - **Requirements:** Requires familiarity with Model Context Protocol servers for effective use.; May require additional software or setup configurations to fully utilize the listed server resources. - **Adopt for:** awesome-mcp-servers is a curated list of Model Context Protocol servers for AI applications, useful when you need specific resources related to MCP and less suitable if your focus is on other protocols. ## Decision facts: awesome-mcp-servers - **Adopt for:** Decision Facts for awesome-mcp-servers ## Choose when ### Choose awesome-mcp-servers if… - Pricing: The pricing model is unknown since the information provided does not specify any costs associated with using awesome-mcp-servers.. - Requirements: Requires familiarity with Model Context Protocol servers for effective use.; May require additional software or setup configurations to fully utilize the listed server resources.. - Tags unique to awesome-mcp-servers: ai, anthropic-claude, tool-use, tools. - Use awesome-mcp-servers if you specifically require access to detailed listings of Model Context Protocol server resources that can be integrated into AI applications. ### Choose awesome-mcp-servers if… - Tags unique to awesome-mcp-servers: anthropic, genai, mcp-server, mcp-server-discovery. - awesome-mcp-servers ships an MCP server manifest. - Need TypeScript-based MCP server implementations and resources. ## When NOT to use awesome-mcp-servers - Avoid using it if your requirements do not align with the Model Context Protocol, opting instead for platforms that support a broader range of protocols. - If you need to focus on different aspects of AI development not covered by MCP resources or prefer real-time data over curated lists, this might not be suitable. ## 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-mcp-servers and awesome-mcp-servers? awesome-mcp-servers: A curated list of Model Context Protocol servers. 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-mcp-servers over awesome-mcp-servers? Choose awesome-mcp-servers over awesome-mcp-servers when Pricing: The pricing model is unknown since the information provided does not specify any costs associated with using awesome-mcp-servers.; Requirements: Requires familiarity with Model Context Protocol servers for effective use.; May require additional software or setup configurations to fully utilize the listed server resources.; Tags unique to awesome-mcp-servers: ai, anthropic-claude, tool-use, tools; Use awesome-mcp-servers if you specifically require access to detailed listings of Model Context Protocol server resources that can be integrated into AI applications. ### When should I choose awesome-mcp-servers over awesome-mcp-servers? Choose awesome-mcp-servers over awesome-mcp-servers when Tags unique to awesome-mcp-servers: anthropic, genai, mcp-server, mcp-server-discovery; awesome-mcp-servers ships an MCP server manifest; Need TypeScript-based MCP server implementations and resources. ### When should I avoid awesome-mcp-servers? Avoid using it if your requirements do not align with the Model Context Protocol, opting instead for platforms that support a broader range of protocols. If you need to focus on different aspects of AI development not covered by MCP resources or prefer real-time data over curated lists, this might not be suitable. ### 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-mcp-servers or awesome-mcp-servers more popular on GitHub? awesome-mcp-servers has more GitHub stars (5,757 vs 790). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-mcp-servers and awesome-mcp-servers open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to awesome-mcp-servers or awesome-mcp-servers? GraphCanon lists graph-backed alternatives at [awesome-mcp-servers alternatives](/tools/appcypher-awesome-mcp-servers/alternatives) and [awesome-mcp-servers alternatives](/tools/tensorblock-awesome-mcp-servers/alternatives) ([awesome-mcp-servers markdown twin](/tools/appcypher-awesome-mcp-servers/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/appcypher-awesome-mcp-servers-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-mcp-servers or awesome-mcp-servers? awesome-mcp-servers: Archived. 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-mcp-servers and awesome-mcp-servers? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-mcp-servers trust report](/tools/appcypher-awesome-mcp-servers/trust); [awesome-mcp-servers trust report](/tools/tensorblock-awesome-mcp-servers/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=appcypher-awesome-mcp-servers`](/api/graphcanon/graph?tool=appcypher-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/_