mcp-framework

Rust framework for building AI agents that communicate with Model Context Protocol (MCP) servers via an MCP client (HTTP and stdio) and that can also expose custom tools via an MCP server. Includes example agent integrations for Anthropic (Claude) and OpenAI, plus a web-based inspector for debugging MCP servers/tools.

Evaluated Mar 30, 2026 (22d ago)
Repo ↗ DevTools ai-ml devtools agentic-ai mcp rust mcp-client mcp-server tooling observability inspector
⚙ Agent Friendliness
58
/ 100
Can an agent use this?
🔒 Security
45
/ 100
Is it safe for agents?
⚡ Reliability
28
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
70
Documentation
70
Error Messages
--
Auth Simplicity
75
Rate Limits
10

🔒 Security

TLS Enforcement
60
Auth Strength
35
Scope Granularity
20
Dep. Hygiene
40
Secret Handling
70

TLS is not explicitly documented in the README for HTTP MCP transport; a score reflects likely typical HTTPS use but lacks proof. Authentication for MCP is marked planned; only LLM API key configuration is evidenced. Scope granularity for access control is not described. Rust helps with memory safety, but dependency/Vulnerability hygiene and secret-logging behavior are not documented; .env usage suggests a reasonable baseline for secret handling without showing logging practices.

⚡ Reliability

Uptime/SLA
0
Version Stability
35
Breaking Changes
35
Error Recovery
40
AF Security Reliability

Best When

You want a Rust-first, async (Tokio) MCP client/server toolkit with example code for common agent/model integrations and local debugging via an inspector.

Avoid When

You require fully implemented MCP extensions like resources/prompts/auth/memory (these are described as planned/Not implemented yet) or you need strong, documented rate-limit/retry semantics from the framework itself.

Use Cases

  • Build MCP-backed AI agents that can call external tools exposed via MCP servers
  • Create custom MCP servers that wrap business logic/APIs as agent tools
  • Run multi-server MCP orchestration from a single agent
  • Develop and debug MCP tools via a web inspector UI
  • Prototype browser automation tasks through MCP integrations (e.g., Playwright MCP)

Not For

  • Production use cases requiring formally published SLAs/operational guarantees (not evidenced here)
  • Teams needing a managed hosted SaaS offering (this appears to be a self-hosted Rust library/framework)
  • Use cases requiring first-class OAuth/API gateway features for the MCP framework itself (authentication is marked as planned)

Interface

REST API
No
GraphQL
No
gRPC
No
MCP Server
Yes
SDK
Yes
Webhooks
No

Authentication

Methods: Environment variable API keys for Anthropic and/or OpenAI (as shown via .env usage)
OAuth: No Scopes: No

README indicates LLM API credentials are configured via .env. It also states MCP authentication is planned, not implemented/shipped per the provided README.

Pricing

Free tier: No
Requires CC: No

No pricing information provided (appears to be an open-source library under MIT). LLM/provider costs would apply separately in real deployments.

Agent Metadata

Pagination
none
Idempotent
False
Retry Guidance
Not documented

Known Gotchas

  • Authentication for MCP is described as planned, so deployments may need to rely on network controls or custom solutions for access control.
  • MCP capabilities like resources/prompts are listed as planned/not implemented, so agent designs should avoid relying on them yet.
  • Streaming support is marked planned, so long-running tool/LLM interactions may not behave as token-streaming users expect.

Alternatives

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Scores are editorial opinions as of 2026-03-30.

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