FastMCP
The fast, Pythonic way to build MCP servers and clients
- Source repo
- PrefectHQ/fastmcp
- Stars
- ★ 28k
- Last updated
- today
- License
- Apache-2.0
- Primary language
- Python
- FA score
- 43/100 · Major gaps
At a glance
- How it runs
- Works with
- Universal · cross-platform
- Cost
- Free tier plus a paid hosted plan
- Setup effort
- Low · running in minutes
- You'll need
- Typical use
- Developers who want to quickly expose Python functions as MCP tools for LLM consumption
- Not a fit if
- Teams needing SSO, RBAC, and audit logs (paid Prefect Horizon)
- TypeScript developers wanting an MCP framework (use fastmcp-ts)
- Non-English speakers who need localized documentation
- Source review
- 43/100 · Major gaps 8 safety controls not found
What does this agent do, and when should you use it?
FastMCP is a full-featured framework for building Model Context Protocol (MCP) applications, covering servers, clients, and interactive apps. It automatically turns Python functions into MCP-compliant tools with schema, validation, and documentation generated automatically. It also manages transport negotiation, authentication, and protocol lifecycle when connecting to servers. FastMCP provides three pillars: Servers, Apps (interactive UIs in conversation), and Clients. It is the standard framework for MCP development, with FastMCP 1.0 incorporated into the official MCP Python SDK in 2024.
FastMCP wraps Python functions as MCP tools using decorators like @mcp.tool, and handles protocol lifecycle automatically. Clients can connect to any MCP server via URL, supporting local and remote connections. Apps feature allows interactive UIs to be rendered directly in the conversation. It provides both programmatic and CLI interfaces. Installation is via uv: 'uv add fastmcp'. A server can be started with mcp.run().
- Developers who want to quickly expose Python functions as MCP tools for LLM consumption
- Teams needing to connect multiple MCP servers and manage them centrally
- App developers building interactive tools with UIs rendered in the chat
- Platform engineers deploying MCP servers at scale, considering Prefect Horizon for governance
- TypeScript developers who want parity with FastMCP via the official FastMCP-ts package
How do you install or deploy this agent?
Recommended installation with uv: 'uv add fastmcp'. Ensure Python is available. For full instructions, see the Installation Guide at gofastmcp.com.
How do you use this agent?
Create a Python file, import FastMCP, instantiate a FastMCP object, define tool functions with @mcp.tool, and call mcp.run() to start the server. For a quickstart, refer to gofastmcp.com/getting-started/quickstart.
What are this agent's strengths and limitations?
- Automatic schema, validation, and documentation generation for tools
- Covers the full MCP application stack: servers, clients, and apps
- Incorporated into the official MCP Python SDK, indicating maturity and adoption
- TypeScript counterpart available for cross-language consistency
- Built-in best practices simplify transport negotiation and authentication
- Learning curve for MCP protocol and FastMCP-specific APIs
- Advanced features like Horizon may require a commercial license
- Upgrades may require code adjustments (e.g., from v2 to v3)
- Documentation primarily in English, which may be a barrier for non-English speakers
How does this agent compare with similar options?
FastMCP is the standard framework in the MCP ecosystem, closely tied to the official MCP SDK. For TypeScript, FastMCP-ts is the official counterpart. It competes with lower-level SDKs that require more manual protocol handling.
Key facts side by side with the most closely related agents.
| Agent | Source review | Form / cost | Stars | Updated | Language | Full support on |
|---|---|---|---|---|---|---|
| FastMCP This agent | 43 · Major gaps | Library / SDKFreemium | ★ 28k | today | Python | — |
| BeeAI Framework | 51 · Major gaps | Library / SDKFree + model costs | ★ 3.4k | today | Python | — |
| Jevbridge Decision Sidecar | 62 · Some gaps | CLIFree + model costs | ★ 48 | 28d ago | TypeScript | Codex · OpenAI API · Claude API |
| Microsoft Agent Framework Hands-On Samples | 50 · Major gaps | Library / SDKFree + model costs | ★ 385 | 4mo ago | Jupyter Notebook | — |
How does FollowAgents rate this agent?
Why each dimension lost points
Evidence shows an MCP framework but no implementation or documentation for permission management, user confirmation, data flow transparency, sensitive data handling, dependency security, external effects, rollback, or source attribution. Hence all trust criteria score 0.
Self-consistency: README, pyproject.toml, and SECURITY.md are consistent in description and version support, score 2. Dependency availability: pyproject.toml lists dependencies and version constraints but no lock file or verification mechanism, score 2. Failure messages: No documentation on error handling or user prompts, score 1.
Audience and scenarios: README clearly defines three scenarios: servers, clients, and apps, score 2. Capability boundaries: Documentation describes the framework's scope but not explicit limitations, score 2. Trigger precision: Tool and resource definitions are clear but no trigger mechanisms, score 2. Environment fit: Supports Python 3.10+ but no OS or deployment environment mentioned, score 2.
Information architecture: README and documentation links are clear, score 2. Install notes: Provides uv install command, score 2. Naming stability: Project name and API naming are consistent, score 2. Examples and FAQ: Provides example code but no FAQ, score 2. Known limitations: Not explicitly listed, score 1. License: Apache-2.0, score 2. Versioning and changelog: Has upgrade guides but no changelog, score 2. Maintenance responsibility: Author and Prefect company are clear, score 2.
Output usability: Tool and resource output formats are clear, score 2. Marginal value: Framework provides automated schema and protocol handling, score 2. Cost benefit: Open source and free, score 2.
Claim traceability: Claims in README lack specific evidence, score 1. Cross-source corroboration: Relies on single source, score 1. Fact-inference separation: Not clearly distinguished, score 1.
- Not found in source: least-privilege scopingGrant only what the task needs: a dedicated account or read-only token, scoped to specific directories and repos.
- Not found in source: confirmation before actingTurn on (or add) a confirmation step before it acts, and try it in a sandbox or test environment before real data.
- Not found in source: data-flow disclosureWatch which external services it contacts (proxy or firewall logs) and keep sensitive data out until you know where it goes.
- Not found in source: sensitive-data handlingUse dedicated, low-privilege, revocable API keys — never production credentials — and keep secrets out of logs.
- Not found in source: dependency securityPin versions and run a dependency audit (npm audit, pip-audit) before installing; prefer running it in a container.
- Not found in source: disclosed external effectsEstablish which external systems it writes to, sends to or changes, and verify with test accounts or repos before production.
- Not found in source: rollback or recovery pathBack up first, or work on a git branch or snapshot, so its changes can be undone.
- Not found in source: verifiable attributionInstall from the official repo or registry and check the publisher and URL to avoid look-alike packages.
- No security mechanisms such as permission management, user confirmation, or data flow transparency are provided; assess before use.
- Dependency security is not verified; consider checking dependency locking and vulnerability scanning.
- No rollback mechanism is provided; back up before upgrading.
- Known limitations are not explicitly stated; potential compatibility issues may be hidden.
Recent releases
Latest entries from the project's GitHub Releases. Notes are quoted from upstream as written, not rewritten or tested by FollowAgents.
-
v4.1.1 v4.1.1: Regex Marks the Spot
Release notes excerpt
Regex tool search now rejects patterns over 1,000 characters and stops after about a second, and SkillsDirectoryProvider discovers skill folders that are links again, including links to folders outside the skills root; a skill's own files must still resolve inside the folder it links to. All 4.x users are encouraged to upgrade. Thanks to our 4 contributors, including 1 first-time contributor. <!-- Release notes generated using configuration in .github/release.yml at main --> What's Changed Security 🔒 …View on GitHub ↗ -
v3.4.9 v3.4.9: Contain Yourself
Release notes excerpt
This release backports security fixes from 4.1: OpenAPI path parameters reject . and .. segments, a skill's SKILL.md must stay inside its skill folder, regex tool search is bounded in time and pattern length, and JWT verifiers share JWKS refreshes instead of fetching on every unknown key ID. All 3.x users are encouraged to upgrade. Thanks to our 6 contributors, including 3 first-time contributors. <!-- Release notes generated using configuration in .github/release.yml at release/3.x --> What's Changed Security 🔒 …View on GitHub ↗ -
v4.1.0 v4.1.0: Fourth and One
Release notes excerpt
FastMCP 4.1.0 is a maintenance release at heart: a broad sweep of fixes across OpenAPI, proxies, auth, tasks, and the CLI, plus full Python 3.15 support. It doesn't change how most servers behave. A few security fixes do tighten inputs that FastMCP previously accepted, though, and our versioning policy keeps breaking changes out of patch releases, so this ships as a point-one release. Check these before upgrading: - MultiAuth now qualifies client IDs by source, so existing MultiAuth sessions and tasks start new ownership scopes. Finish pending tasks before upgrading. …View on GitHub ↗