Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Force evidence-gated, tiered claim reporting (FACT/INFERENCE/SPECULATION). No-LLM.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"verify-claim": {
"command": "uvx",
"args": [
"mcp-verify-claim"
]
}
}
}在终端中运行这条命令
claude mcp add verify-claim -- uvx mcp-verify-claim粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"verify-claim": {
"command": "uvx",
"args": [
"mcp-verify-claim"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"verify-claim": {
"type": "stdio",
"command": "uvx",
"args": [
"mcp-verify-claim"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
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这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 sudo-ai-git 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(1.0.0)于2个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。
同一分类中有:Context7, Codebase Memory, Exa
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
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按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
A Model Context Protocol (MCP) server that forces evidence-gated, honestly tiered claim reporting. Every claim an agent makes gets classified into an evidence tier (FACT / INFERENCE / SPECULATION / UNVERIFIED) with attached evidence — the antidote to the silent-unverified-claim failure mode ("pushed successfully", "the tests pass", "the API returned 200" — asserted without ever running the command).
Deterministic, no LLM, no network calls. Self-hostable, MCP-compatible with any agent (Claude Code, Cursor, Copilot, OpenClaw, Codex CLI).
The most common agent failure is not wrong reasoning — it's reporting a plausible-sounding *result that was never verified*. mcp-verify-claim installs a hard gate: no unverified claim can be reported as fact.
When you give an agent access to real operations (edits, checks, rule evaluation, mutations) through MCP, the value is that it can answer with evidence instead of opinion — it ran the check, it saw the real state, it can prove what it did. But that only holds if the agent is *forced* to attach the evidence. A rules-and-checks surface ("is the module valid?", "did this state change slice apply?", "what actually changed?") is exactly the high-value case: each check produces a machine-verifiable result.
mcp-verify-claim is the gate that guarantees the agent reports the result with its evidence attached (exit code, real read-back, actual HTTP status) and cannot pass off a guess or an unrun step as truth. Pair it with any MCP surface that exposes operations, and the agent's answers become auditable, line-by-line, instead of plausible.
tier_claim(claim, evidence, verification_kind) — classify a claim into a tier + verdict (TRUST / REVIEW / DO-NOT-REPORT) + honest next-action.check_claim(claim) — deterministic scan for fabrication/hedging signals (completion-without-artifact, "the API returned", hedge words).report_templates() — the canonical STATUS / EVIDENCE / GAPS completion shape and the 6-step behavioral loop.tier_definitions() — the FACT / INFERENCE / SPECULATION / UNVERIFIED definitions.| Tier | Meaning | Verdict |
|---|---|---|
| FACT | Saw it in raw tool output (exit code, body, file read-back, HTTP status) | TRUST |
| INFERENCE | Deduced from facts; show the chain | REVIEW |
| SPECULATION | A guess; never report as truth | REVIEW |
| UNVERIFIED | No evidence produced | DO-NOT-REPORT |
One command (recommended) — installs from the repo, no PyPI token needed:
uv tool install git+https://github.com/sudo-ai-git/mcp-verify-claim
mcp-verify-claim # run stdio server mcp-verify-claim --http --port 8137 # or Streamable HTTP for remote use
Or with pipx: pipx install git+https://github.com/sudo-ai-git/mcp-verify-claim
Direct from source (fallback):
pip install mcp
python3 mcp_server.py
{ "mcpServers": {
"verify-claim": { "command": "mcp-verify-claim", "args": [] } }}
tier_claim("Successfully deployed", evidence="", verification_kind="")
--> tier UNVERIFIED, verdict DO-NOT-REPORT signals: [high] completion claim without artifact next: go get the evidence before reporting
tier_claim("Deploy is live", evidence="origin/main SHA==local HEAD, HTTP 200", verification_kind="read_back") --> tier FACT, verdict TRUST
This is one of three deterministic, no-LLM agent-trust MCP servers by sudo-ai-git:
mcp-skill-sec — pre-install skill/security auditmcp-verify-claim — evidence-gated, honestly-tiered claim reporting (this repo)mcp-benchmark-hygiene — pytest config-leakage / eval-honesty detectionSibling product: mcp-token-saver — token-cost proxy + analyzer for agent conversations (dedupes redundant tokens before they're billed; live-proven 74% cut). Discussion
Also in the family (a free CLI, not an MCP server): harness-audit — deterministic agent-eval / benchmark-grading hygiene audit that catches the same silent config-leakage mis-scoring class. Free lead-magnet; the same verification discipline, zero dependencies, auditable line-by-line.
MIT. Written by sudo-ai-git. Standalone behavioral-rigor tool; encodes no proprietary method. MCP expression of the verify-before-claim agent skill.
mcp-name: io.github.sudo-ai-git/mcp-verify-claim
Need this connected to *your* internal system (auth, logging, security-scan pass, hosted)? Open a custom-build request. MIT reference assets are free to use either way.