--- title: "mcpc vs fastmcp" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/apify-mcpc-vs-prefecthq-fastmcp" tools: ["apify-mcpc", "prefecthq-fastmcp"] --- # mcpc vs fastmcp *GraphCanon updated Sep 20, 2026* ## Verdict Pick mcpc if mcpc is a CLI client for interacting with Model Context Protocol in TypeScript, providing support for persistent sessions, OAuth 2.1, task handling, JSON output, and proxy capabilities; pick fastmcp if fastmcp is a Python library for building MCP servers and clients, designed to facilitate the Model Context Protocol (MCP) in AI development. [mcpc](https://npmjs.com/package/@apify/mcpc) reports 890 GitHub stars, 88 forks, and 24 open issues, last pushed Sep 19, 2026. [fastmcp](https://gofastmcp.com) has 28k stars, 2.4k forks, and 345 open issues, last pushed Sep 17, 2026. Figures are from public GitHub metadata via [mcpc's repository](https://github.com/apify/mcpc) and [fastmcp's repository](https://github.com/PrefectHQ/fastmcp). | | [mcpc](/tools/apify-mcpc.md) | [fastmcp](/tools/prefecthq-fastmcp.md) | | --- | --- | --- | | Tagline | CLI client for MCP protocol with support for persistent sessions, OAuth, tasks, JSON output, and proxy. | The fast, Pythonic way to build MCP servers and clients | | Stars | 890 | 27,718 | | Forks | 88 | 2,352 | | Open issues | 24 | 345 | | Language | TypeScript | Python | | Adopt for | mcpc is a CLI client for interacting with Model Context Protocol in TypeScript, providing support for persistent sessions, OAuth 2.1, task handling, JSON output, and proxy capabilities. | fastmcp is a Python library for building MCP servers and clients, designed to facilitate the Model Context Protocol (MCP) in AI development. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | fastmcp is licensed under the Apache-2.0 license, allowing for broad use in both open-source and commercial projects. | | Categories | AI Agents, Developer Tools | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [mcpc](/tools/apify-mcpc.md) | [fastmcp](/tools/prefecthq-fastmcp.md) | | --- | --- | --- | | Open issues (now) | 24 | 345 | | Stars delta | +157 (30d) | +872 (30d) | | Open issues delta | +6 (30d) | +80 (30d) | | Full report | [trust report](/tools/apify-mcpc/trust.md) | [trust report](/tools/prefecthq-fastmcp/trust.md) | ## Decision facts: mcpc - **Requirements:** Does not require Docker, can be integrated easily within environments without Docker support. - **Adopt for:** mcpc is a CLI client for interacting with Model Context Protocol in TypeScript, providing support for persistent sessions, OAuth 2.1, task handling, JSON output, and proxy capabilities. - **License detail:** Apache-2.0 ## Decision facts: fastmcp - **Requirements:** fastmcp can be added to your project using the uv package manager, but full installation instructions are available on the official documentation. - **Adopt for:** fastmcp is a Python library for building MCP servers and clients, designed to facilitate the Model Context Protocol (MCP) in AI development. - **License detail:** fastmcp is licensed under the Apache-2.0 license, allowing for broad use in both open-source and commercial projects. ## Choose when ### Choose mcpc if… - mcpc is primarily TypeScript; fastmcp is Python. - Requirements: Does not require Docker, can be integrated easily within environments without Docker support.. - Tags unique to mcpc: ai-agents, cli, command-line, mcp-client. - mcpc ships an MCP server manifest. - If you require a command-line interface compatible with the Model Context Protocol to manage AI agents or workflows involving TypeScript code execution and task handling. ### Choose fastmcp if… - fastmcp is primarily Python; mcpc is TypeScript. - Requirements: fastmcp can be added to your project using the uv package manager, but full installation instructions are available on the official documentation.. - Tags unique to fastmcp: agents, fastmcp, llms, mcp. - Use fastmcp when you need to build MCP servers and clients in Python, as it provides a streamlined and Pythonic approach to implementing the Model Context Protocol. ## When NOT to use mcpc - In scenarios that specifically demand a graphical user interface over CLI, as mcpc solely offers terminal-based operations with no GUI alternative. - If your project strictly uses languages other than TypeScript or has no need for the MCP protocol, considering mcpc's capabilities are built around these. ## When NOT to use fastmcp - Avoid fastmcp if your project does not require the Model Context Protocol (MCP), as it is specialized for this protocol and may introduce unnecessary complexity. - Do not use fastmcp if you are working in a language other than Python, as it is a Python-specific library and will not be compatible with other languages. ## Common questions ### What is the difference between mcpc and fastmcp? mcpc: CLI client for MCP protocol with support for persistent sessions, OAuth, tasks, JSON output, and proxy.. fastmcp: The fast, Pythonic way to build MCP servers and clients. See the comparison table for live GitHub stats and shared categories. ### When should I choose mcpc over fastmcp? Choose mcpc over fastmcp when mcpc is primarily TypeScript; fastmcp is Python; Requirements: Does not require Docker, can be integrated easily within environments without Docker support.; Tags unique to mcpc: ai-agents, cli, command-line, mcp-client; mcpc ships an MCP server manifest; If you require a command-line interface compatible with the Model Context Protocol to manage AI agents or workflows involving TypeScript code execution and task handling. ### When should I choose fastmcp over mcpc? Choose fastmcp over mcpc when fastmcp is primarily Python; mcpc is TypeScript; Requirements: fastmcp can be added to your project using the uv package manager, but full installation instructions are available on the official documentation.; Tags unique to fastmcp: agents, fastmcp, llms, mcp; Use fastmcp when you need to build MCP servers and clients in Python, as it provides a streamlined and Pythonic approach to implementing the Model Context Protocol. ### When should I avoid mcpc? In scenarios that specifically demand a graphical user interface over CLI, as mcpc solely offers terminal-based operations with no GUI alternative. If your project strictly uses languages other than TypeScript or has no need for the MCP protocol, considering mcpc's capabilities are built around these. ### When should I avoid fastmcp? Avoid fastmcp if your project does not require the Model Context Protocol (MCP), as it is specialized for this protocol and may introduce unnecessary complexity. Do not use fastmcp if you are working in a language other than Python, as it is a Python-specific library and will not be compatible with other languages. ### Is mcpc or fastmcp more popular on GitHub? fastmcp has more GitHub stars (27,718 vs 890). Stars measure visibility, not whether either tool fits your constraints. ### Are mcpc and fastmcp open source? Yes - both are open-source projects on GitHub (mcpc: Apache-2.0, fastmcp: Apache-2.0). ### Where can I find alternatives to mcpc or fastmcp? GraphCanon lists graph-backed alternatives at [mcpc alternatives](/tools/apify-mcpc/alternatives) and [fastmcp alternatives](/tools/prefecthq-fastmcp/alternatives) ([mcpc markdown twin](/tools/apify-mcpc/alternatives.md), [fastmcp markdown twin](/tools/prefecthq-fastmcp/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/apify-mcpc-vs-prefecthq-fastmcp.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, mcpc or fastmcp? mcpc: Very active. fastmcp: 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 mcpc and fastmcp? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [mcpc trust report](/tools/apify-mcpc/trust); [fastmcp trust report](/tools/prefecthq-fastmcp/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=apify-mcpc`](/api/graphcanon/graph?tool=apify-mcpc) - 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/_