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PolicySignal

A Model Context Protocol (MCP) server for searching and analyzing the public discourse of Xi Jinping — speeches, articles, and official statements as published on open government sources. Neutral research infrastructure for China-watchers, academics, journalists, and analysts. Any MCP-compatible client — Claude Desktop, Claude Code, ChatGPT, Cursor, VS Code, Cline, Windsurf — can connect over a single public URL.

中文说明见 README.zh.md · Full setup & tool reference: USER-GUIDE.md / 使用指南.md

What this is: a retrieval and discourse-analysis tool over publicly available official texts — it surfaces what was said, when, and how phrasing evolves, with verbatim, source-linked citations. What this is not: not a prediction service, not an endorsement, not a tool for profiling private individuals. Analytical outputs are labeled research inference, never fabricated quotes or claims of certainty. In the tradition of open China-studies tooling such as the China Media Project and CSIS Interpret: China.


Quick start

The server is a public, remote, no-auth MCP endpoint — most clients need only the URL:

https://policy-signal.onrender.com/mcp
  • Claude Code (fastest): claude mcp add --transport http --scope user policy-signal https://policy-signal.onrender.com/mcp

  • Claude Desktop / ChatGPT / Cursor / VS Code / Cline / Windsurf: add a custom / remote MCP connector and paste the URL above (no authentication). Per-client steps in USER-GUIDE.md.

Then ask your assistant, for example:

"Using policy-signal, chart the phrase trend of 新质生产力 vs 高质量发展 by year, and quote the key passage with its source."

Related MCP server: Bidding MCP Server

Capabilities

Tool

What it does

search / list_articles

Full-text search (synonym/OR sets, time-sorted) with metadata filters

get_article / get_context

Retrieve a document / close-read a passage — the only source of verbatim quotes

topic_timeline

Evidence timeline of how a topic's framing evolves year over year

phrase_trend

Track a formulation's rise / fall / disappearance over time (tifa signal; zero-filled buckets so "no longer mentioned" is visible)

recent_signals

Scan for recently rising or newly appearing formulations

corpus_stats / update_corpus

Coverage & freshness / incremental refresh (refresh disabled on the public endpoint)

Two guided prompts — scenario_research(topic) and event_prediction(event) — walk a client model through an evidence-first method: build a timeline → compare formulations → close-read turning points → layered high/medium/low-confidence inference with explicit falsification points.

Method & guardrails

  • Every claim is anchored to a document (id + date + source URL). Verbatim quotes come only from get_context / get_article, checked against the corpus.

  • Facts vs. inference are labeled separately. The analytical prompts forecast themes, framing, and formulation priorities — never a verbatim script, a specific dated event, or a probability of an act.

  • Research framing. Outputs are documentary research over public statements, not prophecy.

Corpus & sources

Public official statements as published on open government sources; see SOURCES.md. The corpus stores document text and metadata for search and citation and is not offered as a bulk-download dataset; every result links back to its original publication. Usage limits and troubleshooting are in USER-GUIDE.md.

Disclaimer

Independent research infrastructure published by ACEE Ventures for educational and analytical use. It analyzes publicly available official statements and makes no claim to represent, predict, or endorse any person or government; it is not affiliated with or endorsed by any government or official body. Analytical outputs are research inference and should not be treated as factual predictions. See DISCLAIMER.md.

License

Code: MIT. Corpus text remains the property of its original publishers, used here for research and citation; this repository does not grant rights to redistribute source texts.


Maintained by ACEE Ventures.

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