MCP server for CNINFO A-share announcement download, parsing and search
Wellknown found it in public sources; nobody has proven control of it yet. Claiming takes one click if the repository is under your GitHub account, or a small file on your domain otherwise. Verified owners get the badge, 15-minute checks, status alerts, edits that outrank crawled data, and a ranking boost.
Agents can do it too: POST https://wellknown.network/api/v1/claims with {"agent":"agentladle-mcp-cninfo","method":"well_known_file"} — machine-readable steps at claim.json, guide at /docs/claim.
Everything here was measured by our prober or read from a registry. Nothing is self-reported.
Attributed to the source that supplied each field. Treated as claims, not facts.
# AgentLadle MCP CNINFO **English** | [中文](README_zh.md) > 🇨🇳 **China A-Share Annual Reports** — Cloud-hosted MCP for Shanghai & Shenzhen listed companies. [Read more](Chinese-A-share-MCP-README.md) | [Get API Key](https://agentladle.com/register) A [MCP (Model Context Protocol)](https://modelcontextprotocol.io/) server that provides tools for **discovering, downloading, parsing, and searching** China A-share announcements from [CNINFO (巨潮资讯网)](http://www.cninfo.com.cn). It enables AI assistants (Claude, Cursor, etc.) to access CNINFO announcement data through 6 structured tools — from discovering available announcements to keyword-searching within their pages. > **Scope (v0.1):** Announcements only. Periodic reports (年报 / 半年报 / 一季报 / 三季报) are out of scope. ## Features - **6 MCP tools** for CNINFO announcement data: state-driven retrieval (search directly, fallback to download/parse only when needed) - **PDF document parsing** using [PyMuPDF](https://pymupdf.readthedocs.io/) — physical page extraction into page-split JSON - **Local keyword search** with TF + position-boost scoring, zero external search dependencies - **Idempotent** — already-downloaded/parsed files are automatically skipped - **Zero-config install** — one line to add to your MCP client, no clone or manual setup needed - **Pure Python**, cross-platform (Windows / macOS / Linux) ## Prerequisites - **Python 3.10+** — [Download Python](https://www.python.org/downloads/) - **uv** — [Install uv](https://docs.astral.sh/uv/getting-started/installation/) > **Note:** After installing uv, restart your terminal and MCP client (e.g. Cherry Studio) to ensure the `uv` command is recognized. ## Quick Start Add to your MCP client configuration (Claude Desktop, Cursor, etc.): ```json { "mcpServers": { "mcp-cninfo": { "command": "uvx", "args": ["agentladle-mcp-cninfo"] } } } ``` That's it. `uvx` will automatically download the package and its dependencies from PyPI — no clone, …
Mapped onto the structured taxonomy from declared text and observed tool names. Confidence shown for derived entries.
Every source is kept verbatim. Field changes are logged as events.