Devnors Data - MCP Server: MCP,Model Context Protocol,Claude,Cursor,WorkBuddy,接口,数据API,裁判文书,Legal Case,法律法规,法条,Law Article,企业工商,Company Registry,企业年报,Annual Report,税号开票,Tax Invoice,失信核查,被执行人,关键词指数,微信指
View on GitHub ↗Use Devnors Data in MCP clients such as Codex, Claude Desktop, Cursor, WorkBuddy, and other AI assistant tools.
Devnors Data MCP helps your assistant discover available capabilities, inspect required parameters, and call legal / enterprise / content / express APIs with your Devnors Data API Key.
You can use Devnors Data MCP with any MCP-compatible client that supports remote HTTP or local stdio servers, including:
- Codex - Claude Desktop - Cursor - WorkBuddy - Other MCP-compatible AI assistants
For Codex, add Devnors Data as a remote MCP server and use the Remote HTTP URL and Authorization header below.
Remote HTTP is the recommended way to use Devnors Data MCP. No local Python install is required.
Create an API Key in the developer console.
You can also run the MCP server locally after pip install devnors-mcp.
On Windows, client PATH often cannot find devnors-mcp. Prefer the python -m form above, or set command to an absolute Python path.
Use your Devnors Data API Key in one of these ways:
Bearer … is the recommended Authorization format.
Optional private / self-hosted base URL for local stdio:
The assistant can call listcapabilities first, explain required parameters, invoke the selected tool after you provide values, and help interpret common error codes.
Tool Description ------ listcapabilities Discover live domain/type, filters, fields, examples, errors legalcasesearch Legal judgment documents legallawsearch Current law articles contentkeywordindex Keyword traffic index contentkeywordexpand Keyword expansion contentwechatindex WeChat Index contenthotrank
From the project README.
Add the radar badge to your README — it shows your project was picked up by MCP Radar and links to this page:
[](https://mcp.liqiwa.com/s/DevnorsAI--devnors-data-mcp.html)
Turn scattered notes, docs and transcripts into a queryable Markdown wiki — an LLM knowledge-base compiler with MCP access, no embeddings, self-hosted.
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