MCP.so
登录
C

Costwright Mcp

@hernaninverso

代码仓库

关于 Costwright Mcp

Static worst-case token-budget analysis of LLM-agent workflows

基本信息

分类

AI 与智能体

传输方式

stdio

发布者

hernaninverso

提交者

Hernán Inverso

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "costwright": {
      "command": "npx",
      "args": [
        "-y",
        "costwright-mcp"
      ],
      "env": {
        "COSTWRIGHT_API_KEY": "your_rapidapi_key"
      }
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Costwright Mcp?

Costwright Mcp is a static worst-case token‑budget analyzer for LLM‑agent workflows. It examines a Python repository that uses LangGraph, CrewAI, or the OpenAI Agents SDK and reports – by pure AST analysis, without running the code – the worst‑case budget ceiling of every workflow graph. It can optionally issue an Ed25519‑signed budget certificate that is logged to a public transparency log.

How to use Costwright Mcp?

Configure the MCP server using npx costwright-mcp with the COSTWRIGHT_API_KEY environment variable. Four tools are provided: costwright_check (static analysis), costwright_certify (signed certificate), costwright_verify (public certificate verification), and costwright_pubkey (retrieve public keys). The verify and pubkey tools require no API key.

Key features of Costwright Mcp

  • Static worst‑case token‑budget analysis for LLM agent workflows.
  • Reports certifiable, default‑dependent, non‑certifiable, and runaway units.
  • Issues Ed25519‑signed budget certificates logged to a transparency log.
  • Pure AST analysis – no code execution required.
  • Compatible with LangGraph, CrewAI, and OpenAI Agents SDK.
  • Public verify and pubkey tools for offline verification.

Use cases of Costwright Mcp

  • Catch missing token caps before deploying an agent workflow.
  • Identify while True: runaway drivers in LLM agent code.
  • Provide a “budget type check” for agent workflow pipelines.
  • Issue signed budget certificates for compliance or auditing.

FAQ from Costwright Mcp

What kind of repositories does Costwright Mcp analyze?

It analyzes Python repositories that use LangGraph, CrewAI, or the OpenAI Agents SDK, returning worst‑case token budgets for every workflow graph.

Does Costwright Mcp run the code it analyzes?

No. It performs pure static AST analysis – the code is never executed.

Is an API key required to use Costwright Mcp?

Yes, for the check and certify tools. The verify and pubkey tools are public and require no key.

Where does my source code go when using Costwright Mcp?

The check and certify tools upload a compressed archive of the repository to the hosted API. See the privacy policy at https://eleata.io/privacy/ for details.

What output does Costwright Mcp produce?

It returns a pass/fail status along with counts of units categorized as certifiable, default‑dependent, non‑certifiable, or runaway, and identifies which LLM calls have no token cap.

评论

AI 与智能体 分类下的更多 MCP 服务器

21st.dev Magic AI Agent

21st-dev

It's like v0 but in your Cursor/WindSurf/Cline. 21st dev Magic MCP server for working with your frontend like Magic

5.3K

Just Prompt - A lightweight MCP server for LLM providers

disler

just-prompt is an MCP server that provides a unified interface to top LLM providers (OpenAI, Anthropic, Google Gemini, Groq, DeepSeek, and Ollama)

733

欢迎来到 智言平台

Shy2593666979

AgentChat 是一个基于 LLM 的智能体交流平台，内置默认 Agent 并支持用户自定义 Agent。通过多轮对话和任务协作，Agent 可以理解并协助完成复杂任务。项目集成 LangChain、Function Call、MCP 协议、RAG、Memory、HITL、Skill、Milvus 和 ElasticSearch 等技术，实现高效的知识检索与工具调用，使用 FastAPI 构建高性能后端服务。

797

1MCP - One MCP Server for All

1mcp-app

A unified Model Context Protocol server implementation that aggregates multiple MCP servers into one.

468

MCP Client for Ollama (ollmcp)

jonigl

Harness the power of local LLMs with this TUI MCP Client for Ollama. Featuring all core MCP primitives (tools, prompts, resources), agent mode, multi-server, model switching, streaming responses, human-in-the-loop, thinking mode, model params config, system prompts, and saved pre

768