mcp-registry/io.github.acee-ventures/china-policy-signal · v1.29.0
Also listed as glama/acee-ventures/china-policysignal, glama/acee-ventures/xi-corpus-mcp
As of 2026-10-22 17:22 UTC, the Acee Ventures China Policy Signal MCP server is down with a Glimind reliability score of 38/100 (grade F). Over the last 30 days it answered 0% of Glimind's liveness checks.
Search Chinese government and Party documents: Xi Jinping speeches and articles, 2012 to present.
Point your MCP client at this streamable-http endpoint: https://policy-signal.onrender.com/mcp
The endpoint did not complete an MCP handshake.
Check the URL, TLS certificate and that the server answers a JSON-RPC "initialize" POST. How to fix →
8 of 8 tool(s) carry no readOnlyHint/destructiveHint annotations.
Annotate read-only tools with {"readOnlyHint": true}. Agents and gateways can then run them without a confirmation prompt, and route around destructive ones. How to fix →
27 parameter(s) across 7 tool(s) have no description.
Add a "description" to each parameter with its format and an example ("ISO 8601 date, e.g. 2026-10-17"). This is the commonest cause of wrong arguments on the first call. How to fix →
No tool declares an outputSchema.
Declare outputSchema and return structuredContent (MCP 2025-06-18+). Agents can then parse results without guessing, and chain tools reliably. How to fix →
Paste-ready definitions with the problems above fixed. Changes marked verify need a human look. 7 tool(s) still need parameter descriptions written by someone who knows the API. All of them as JSON: /v1/readiness/mcp-registry%2Fio.github.acee-ventures%2Fchina-policy-signal/fixes
{
"name": "corpus_stats",
"description": "语料库覆盖情况:总篇数、时间范围、来源分布、待抓取/失败数、站点总数对比。",
"inputSchema": {
"type": "object",
"title": "corpus_statsArguments",
"properties": {}
},
"annotations": {
"readOnlyHint": true
}
}{
"name": "get_article",
"description": "按 id 取一篇文章的完整元数据与全文。max_chars>0 时截断正文。",
"inputSchema": {
"type": "object",
"title": "get_articleArguments",
"required": [
"article_id"
],
"properties": {
"max_chars": {
"type": "integer",
"title": "Max Chars",
"default": 0
},
"article_id": {
"type": "integer",
"title": "Article Id"
}
}
},
"annotations": {
"readOnlyHint": true
}
}{
"name": "get_context",
"description": "单篇精读:返回该文章中命中 query 的段落及前后 window 段上下文(带段号)。\n 需要逐字引用原话时,必须从这里或 get_article 的返回文本中原样复制。",
"inputSchema": {
"type": "object",
"title": "get_contextArguments",
"required": [
"article_id",
"query"
],
"properties": {
"query": {
"type": "string",
"title": "Query"
},
"window": {
"type": "integer",
"title": "Window",
"default": 1
},
"article_id": {
"type": "integer",
"title": "Article Id"
}
}
},
"annotations": {
"readOnlyHint": true
}
}Get an email or webhook when this server's readiness drops by 10+ points, tool-poisoning text appears, or a tool breaks:
curl -X POST https://glimind.com/v1/subscriptions -H 'content-type: application/json' -d '{"tools":["mcp-registry/io.github.acee-ventures/china-policy-signal"],"email":"[email protected]"}'Agents: watch_tool({"toolId": "mcp-registry/io.github.acee-ventures/china-policy-signal"}) over MCP.
search ~196 tokenslist_articles ~164 tokensphrase_trend ~142 tokensrecent_signals ~129 tokenstopic_timeline ~116 tokensStatic checks of the advertised tools/list (schema, descriptions, annotations, tool-poisoning patterns, names, size) plus observed protocol, uptime, latency and contract changes. Read-only: no tool is ever called. Weights: schema 15, docs 20, safety 15, efficiency 15, compatibility 15, protocol 5, reliability 10, stability 5. Token counts are estimates (~3.6 characters per token).
Operator? Fix these, then re-check live. Embed the readiness badge:
[](https://glimind.com/server/mcp-registry%2Fio.github.acee-ventures%2Fchina-policy-signal?ref=badge)
<a href="https://glimind.com/server/mcp-registry%2Fio.github.acee-ventures%2Fchina-policy-signal?ref=badge"><img src="https://glimind.com/v1/readiness/badge/mcp-registry%2Fio.github.acee-ventures%2Fchina-policy-signal.svg" alt="MCP agent-readiness"></a>
.. image:: https://glimind.com/v1/readiness/badge/mcp-registry%2Fio.github.acee-ventures%2Fchina-policy-signal.svg :target: https://glimind.com/server/mcp-registry%2Fio.github.acee-ventures%2Fchina-policy-signal?ref=badge :alt: MCP agent-readiness
Glimind records every version of this server's tool definitions in a signed, append-only transparency log. Current manifest sha256:2091159857b1faa9…, first seen 2026-10-17, included at leaf 15936 of 74,150. Version history · verify what your client received.
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Claude Code
claude mcp add --transport http glimind https://glimind.com/mcp
Claude Desktop · Windsurf · Cline (mcpServers JSON)
{
"mcpServers": {
"glimind": {
"type": "http",
"url": "https://glimind.com/mcp"
}
}
}
As of 2026-10-22 17:22 UTC, the Acee Ventures China Policy Signal MCP server is down with a Glimind reliability score of 38/100 (grade F). Over the last 30 days it answered 0% of Glimind's liveness checks.
Acee Ventures China Policy Signal MCP server advertises 11 tools, including corpus_stats, event_prediction, get_article, get_context, list_articles.
Point your MCP client at this streamable-http endpoint: https://policy-signal.onrender.com/mcp
Glimind scanned all 8 tool definitions for tool-poisoning patterns — hidden or invisible characters, instructions that override the model, concealment from the user, requests to read credential or MCP config files, conversation exfiltration and cross-tool shadowing — and found none. This checks what the server tells the model, not what its code does; review the source before granting access to sensitive data.
Status page: 90-day uptime, every outage and how long it lasted.
Claim this listing to get the Verified operator marker, a remediation checklist and owner analytics, or embed the live badge from any of the tool pages above. Maintainers: alerts, deploy attestation and monthly reports.
Status is an automated estimate from Glimind's liveness checks (handshake and tool listing only; no tool is ever called) and may lag or differ from your network. Glimind is not affiliated with this server or its operator. Operator? Request a correction or opt out at https://glimind.com/opt-out.