ToolTrust
C25/100
Smithery

duna-spice-skay-proof

mcpsmithery

@Smithery

# Proof Code-validated pattern intelligence from pydantic-ai's actual source code. ## What It Does Proof extracts working patterns from real library code via analysis — not from documentation, blog posts, or human guesses. 391 patterns from pydantic-ai and pydantic, mapped to a knowledge graph of 1,251 nodes and 8,911 edges. When you ask Proof to build an agent, it assembles code from patterns the library's own code structure validates. If a pattern fails, your feedback makes the network smarter. ## Quick Start No API keys. No auth. No configuration needed. Connect via Smithery CLI npx -y @smithery/cli add proof --transport streamable-http https://mcp.aigentys.com Then in your AI assistant: *"Run catalog() to see what's available."* ## Tools (5) | Tool | Description | |------|-------------| | **catalog()** | List all libraries, pattern counts, and available data. Start here. | | **search(query)** | Find patterns by keyword (e.g., "agent", "tool", "validator"). | | **explain(symbol)** | Deep-dive into a class or function — its methods, dependencies, gotchas. | | **build_agent(description)** | Generate working agent code from validated patterns. | | **report(about, worked, details)** | Report whether generated code worked. Feedback drives confidence scores. | ## How It Works 1. **Graph Engine** loads the knowledge graph (SurrealDB, 1,251 nodes, 8,911 edges) 2. **Pattern Extractor** finds validated patterns from AST analysis of pydantic-ai source 3. **Agent Assembler** composes working code from patterns, not hallucinated guesses 4. **Confidence Scores** start at 0.5 (code-derived) and update with user feedback ## What's in the Network - **pydantic-ai v1.77.0** — 751 classes, 369 functions, 98 docs, 33 examples - **pydantic v2.12.4** — type system, validation, serialization patterns - **391 extracted patterns** — reusable code structures validated by the library itself ## Roadmap Cross-library intelligence (langchain, crewai, OpenAI) is next. Right now it's pydantic-ai + pydantic only. Your feedback is what makes the network smart. Use `report()` after every build.

By Smithery | 10 findings | Scanned 4/19/2026 | tooltrust-scanner/v0.3.8

2 High1 Medium2 Low5 Info

Risk Summary

Needs Approval

Dep Visibility plus Excessive Permissions raises enough risk that this tool should not be auto-trusted.

Potential impact: This finding indicates the tool should be reviewed before it is trusted.

Recommended action: Keep this tool behind manual approval and avoid unattended runs until the risky capabilities are narrowed or removed.

Suggested policy: keep this tool behind manual approval, do not allow unattended runs, and re-scan after narrowing risky permissions.

Security Findings (10)

  • HighAS-002

    ⚠️Excessive Permissions ×2

    tool declares network permission

    search

    tool declares exec permission

    build_agent

    Fix: Tool requests broad permissions (exec/fs/network). Validate input parameters using Enums where possible, and restrict file system operations to explicit allowed directories.

  • MediumAS-002

    ⚠️Excessive Permissions

    search:tool declares db permission

    Fix: Tool requests broad permissions (exec/fs/network). Validate input parameters using Enums where possible, and restrict file system operations to explicit allowed directories.

  • LowAS-011

    ℹ️Missing Rate-Limit / Timeout ×2

    tool performs network or execution operations but declares no rate-limit, timeout, or retry configuration

    searchbuild_agent

    Fix: Declare explicit rate-limit, timeout, and retry configuration for all network and execution tools. Implement exponential back-off and surface resource state to the calling agent.

  • InfoAS-014

    ℹ️Dependency Inventory Unavailable ×5

    Tool did not expose metadata.dependencies or repo_url, so supply-chain coverage is limited.

    catalogsearchexplainbuild_agentreport

    Fix: Review and remediate the identified issue.

Scan this tool yourself

Reproduce this audit locally, integrate into CI, or let your agent audit its own tools.

Install once, then scan any MCP server:

$ curl -sfL https://raw.githubusercontent.com/AgentSafe-AI/tooltrust-scanner/main/install.sh | bash
$ tooltrust-scanner scan --server "npx -y duna-spice-skay-proof"

Adjust the package name if your npm registry name differs from the tool ID. View source

Add badge to your README

Copy this Markdown to show your ToolTrust grade on GitHub.

[![ToolTrust Grade C](https://raw.githubusercontent.com/AgentSafe-AI/tooltrust-directory/main/docs/badges/grade-c.svg)](https://github.com/AgentSafe-AI/tooltrust-directory)