About China PolicySignal
China PolicySignal is a remote MCP server for researching Xi Jinping’s public speeches, articles, and official statements from 2012 onward. It combines full-text search and discourse analysis with citations linked to original documents.
Key features
- 01Search official documents by text and metadata
- 02Retrieve articles and cited passages
- 03Trace topic framing over time
- 04Track phrase frequency and recent signals
- 05Use guided evidence-first research prompts
Use cases
- 01Find dated source passages about a policy topic
- 02Track when a political formulation first appeared
- 03Compare how official framing changes over time
MCP support
The remote MCP server exposes document search, retrieval, timelines, phrase trends, and guided research prompts to MCP clients. Its outputs include document IDs, dates, and source links.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://policy-signal.onrender.com/mcpclaude mcp add --transport http acee-ventures-china-policy-signal https://policy-signal.onrender.com/mcp{"mcpServers":{"acee-ventures-china-policy-signal":{"type":"http","url":"https://policy-signal.onrender.com/mcp"}}}Open in Cursor{"servers":{"acee-ventures-china-policy-signal":{"type":"http","url":"https://policy-signal.onrender.com/mcp"}}}Open in VS Code{"mcpServers":{"acee-ventures-china-policy-signal":{"type":"http","url":"https://policy-signal.onrender.com/mcp"}}}{"mcpServers":{"acee-ventures-china-policy-signal":{"serverUrl":"https://policy-signal.onrender.com/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
Details
From the project READMEChina PolicySignal
Search 14,966 Chinese government and Party documents from your AI assistant — Xi Jinping's speeches, articles, and official statements, 2012 to present, with verbatim source-linked citations.
Remote MCP server. Nothing to install, no API key — just a URL:
https://policy-signal.onrender.com/mcp
Listed in the official MCP Registry as io.github.acee-ventures/china-policy-signal.
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
- 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:
Find the source. "What has Xi said about AI governance? Quote the key passages with dates and source links."
Track a formulation. "Chart how often 新质生产力 (new quality productive forces) appears each year since 2012, and show me the document where it first emerged."
See framing evolve. "Build a timeline of how the framing around 共同富裕 (common prosperity) changed, citing one document per phase."
Each answer comes back with article IDs, publication dates, and links to the original — so every quote can be checked against the source.
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.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.