verify_text
Verify Text
逐声明幻觉核验。输入文本 → 提取声明 → 逐声明验证(supported/refuted/unverified)+ 来源引用。返回红/黄/绿汇总、每条声明的状态/置信度/理由/来源、citations、quota。耗 detect 额度(与 Web 端同源)。
text必填modelspeeddomainstrict
io.github.fredyee由 GitHub 账号 fredyee 发布v0.1.11更新于 Nov 5, 2026
Fact-check LLM outputs with cited sources. API key: aihcc.cloud/keys.
HallucC 用于核验 AI 输出的幻觉与安全风险:逐声明事实核查并附来源、Agent 轨迹评估、动作风险分级。
Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。
把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。
阅读 https://sourceweft.com/mcp/io.github.fredyee%2Fhallucc/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。把它添加到你客户端的 mcpServers 配置中。
{
"mcpServers": {
"hallucc-hallucination-safety-guardian": {
"type": "http",
"url": "https://aihcc.cloud/mcp",
"headers": {
"Authorization": "Bearer <YOUR_TOKEN>"
}
}
}
}中文文档 | Live Demo | Official MCP Registry
[MCP Registry] [npm] [License: MIT] [smithery badge]
Give your AI a fact-checker and a safety gateway: claim-by-claim hallucination detection, agent trajectory evaluation, L0-L3 risk gating for Computer-Use Agent (CUA) actions, Agent source code static audit, and a 40+ feature prompt-injection / jailbreak guard — one MCP server, five tools, works with Claude Code / Cursor / Claude Desktop.
Auth model: each client sends
Authorization: Bearer <your HallucC API key>→ the server forwards it as-is to the backend → the backend validates and deducts from the same account quota as the web app. Keys travel only in HTTP headers — never in tool arguments, never in model transcripts.
check_cua_actionsAn action that leaves task_scope is escalated one level (L0→L1, L1→L2, L2 stays L2 with an "outside task scope" reason appended, L3 unchanged). This mechanism only tightens and never loosens; omitting task_scope has no effect. Credential fields and payment/login domains yield a takeover verdict (suspend and wait for the user to type it themselves — the agent never types your password).
Multi-agent setups (Claude Code Task subagents, Codex agents, Kimi, …): a parent agent reading a credential file (L0 on its own) → a subagent posting it out (L2 on its own) is harmless per hop and dangerous as a chain. Attach the delegation-chain fields to each action and the backend appends a chain_trace: when cross-agent propagation exists the chain aggregate level is raised to L3 and risk_diluted is set (the laundering signal). Leave the chain fields empty and behaviour is bit-for-bit unchanged — existing callers need no change.
The response's ruleset_version lets you verify that online detection and the local Gate run the same rule version.
The MCP server is hosted at https://aihcc.cloud/mcp (remote, streamable-http). Point your client at it with your API key:
Cursor / Claude Desktop work the same way: URL https://aihcc.cloud/mcp, header Authorization: Bearer <key>. Create your API key at https://aihcc.cloud (register → /keys). Free daily quota included.
Same five tools over stdio transport; the key comes from the environment and requests default to the hosted backend https://aihcc.cloud/api.
The base URL must keep the
/apiprefix: nginx only proxies/api/to the backend. A barehttps://aihcc.cloudreaches the frontend instead — the request returns 200 with an HTML body, fails silently (nothing lands in audit or in a fallback file), and the audit replay stays empty.
The server listens on http://127.0.0.1:8787/mcp; health check GET /health.
Settings → MCP → Add MCP server:
httphttp://127.0.0.1:8787/mcp{"Authorization": "Bearer <your HallucC API key>"}~/Library/Application Support/Claude/claude_desktop_config.json:
tools/call (and any non-discovery method) requires a
format-valid key — hc_ + 48 hex — else 401 JSON-RPC, before the backend is contacted.
The format check is a local regex, no backend round-trip.initialize, tools/list, ping, notifications/initialized) stay open
unauthenticated so registries and directory sites can index the server: they make no backend
call and expose no user data. Set MCP_ALLOW_ANON_DISCOVERY=0 to gate those too.verify_api_key; the MCP-layer check only rejects tokens that can't possibly be real keys.quota object (backend quota_status), same source as the web dashboard, decremented per call.check_cua_actions and check_cua_code_audit are both pure rules — no LLM, no quota cost, safe for high-frequency use.Streamable HTTP (the remote transport recommended by the current MCP spec, formerly "HTTP+SSE"), stateless mode: each POST spins up a fresh transport + McpServer and closes when done. Natively supported by Claude Code / Cursor / Claude Desktop. To support legacy SSE-only clients, add SSEServerTransport (dual endpoints /sse + /messages).
io.github.fredyee/hallucc v0.1.11 (active)来源:README.md,提交 4a026de
Verify Text
逐声明幻觉核验。输入文本 → 提取声明 → 逐声明验证(supported/refuted/unverified)+ 来源引用。返回红/黄/绿汇总、每条声明的状态/置信度/理由/来源、citations、quota。耗 detect 额度(与 Web 端同源)。
text必填modelspeeddomainstrictVerify Agent
Agent 输出与轨迹自检。对最终回答跑逐声明幻觉核验,并对执行轨迹做六维结构化评估(事实性/来源/指令合规/工具声明一致/任务完成/反思)。返回 main.claims、steps[].checks、quota。耗 detect 额度。
taskspeedstepsdomainagent_output必填tool_schemasClassify CUA Actions
Computer-Use Agent 动作风险分级。提交动作轨迹 → 逐步返回 L0(放行)/L1(放行+记录)/L2(需确认)/L3(阻断)/takeover(凭据场景挂起等用户亲手输入) 裁决、matched_rules、outcome,及 L0-L3 汇总计数;响应含 ruleset_version(规则库版本)与 disclaimer(本结果仅为分级参考,未执行实际拦截)。覆盖:敏感路径/破坏性命令/不可逆元素语义、域名分级(未知域导航 L2、黑名单域与敏感粘贴到未知域 L3、支付金额超阈值 L3)、凭据词表与支付/登录域 takeover、task_scope 任务意图偏离(越界升一级,只能收窄)、多智能体委托链字段(每条动作可选 chain_id/agent_id/parent_agent_id/delegation_depth,给了则服务端追加链级跨跳污点分析:跨 agent 传播时聚合级别抬到 L3 并置 risk_diluted,返回在 chain_trace 字段;未给则零影响)。纯规则判定,不调 LLM、不耗额度。用于在 agent 执行前/后做安全自检。
actions必填session_idtask_scopeAudit CUA Code
CUA 代码审计:静态分析 Agent 源码,检测危险导入(subprocess/os.system 等)、权限边界(eval/exec)、注入面(字符串拼接 shell)、危险默认值、沙箱缺失。纯规则扫描,不调 LLM、不耗额度。支持单文件或多文件扫描。
codefilesfilenamelanguageCheck Safety
AI 安全网关检测。对 prompt + output 跑 OWASP LLM Top 10 三层检测:40+ 特征规则引擎(注入/越狱/有害内容/敏感信息泄露/欺诈)+ 可选 LLM 深度分析 + 可选幻觉检测。返回 passed、risk_score、risk_level、threats[](category/severity/match_context/recommendation)、quota。fast=true 走纯规则 <10ms 模式。耗 detect 额度(fast 亦计入)。
fastoutput必填promptcheck_hallucinationAgent Ice Wall (Session Fuse)
智能体冰墙(童锁/保险丝):agent 每执行一步前调用一次,做单步幻觉护栏 + 会话级风险累积熔断。响应的 action 字段是唯一需要看的:allow/warn 放行、block 本步拦截、frozen=整场立即停机(风险累积超阈值或命中捏造工具等零容忍项,冻结期间任何动作都不应执行)。熔断条件:block=3分/warn=1分累积 ≥10、连续 3 次 block、或一次命中捏造工具/参数 Schema 违规;冷却 5 分钟自动解冻,或用户手动 reset。session_id 由你在整个 agent 任务内自定复用(状态在云端账号下,本地零安装零存储)。传入 tool_schemas 工具注册表可启用捏造工具/参数校验(强烈建议)。耗额度。与 check_cua_actions(CUA 桌面动作分级)正交:本工具管 LLM agent 的幻觉失控。
step必填tasksession_id必填prior_stepstool_schemasReset Agent Ice Wall
手动解冻被冰墙冻结的 agent 会话(用户确认安全后调用)。was_frozen=false 表示该会话本就没冻结(幂等)。解冻后风险分归零。
session_id必填已满足适用检查项的 100%
该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。
# Claude Codeclaude mcp add --transport http hallucc https://aihcc.cloud/mcp \ --header "Authorization: Bearer <your HallucC API key>"{ "mcpServers": { "hallucc": { "command": "npx", "args": ["-y", "hallucc-mcp"], "env": { "HALLUCC_API_KEY": "<your HallucC API key>" } } }}# 1. Install dependenciesnpm install
# 2. (Optional) configure backend address & port; defaults to local :8001cp .env.example .env# HALLUCC_BASE_URL=http://127.0.0.1:8001# PORT=8787
# 3. Make sure the backend is up: curl http://127.0.0.1:8001/health# 4. Start the MCP server (dev with hot reload)npm run dev# or production: npm startclaude mcp add --transport http hallucc http://127.0.0.1:8787/mcp \ --header "Authorization: Bearer <your HallucC API key>"
claude mcp list# then in conversation: ask Claude to fact-check a passage or scan a prompt for injection{ "mcpServers": { "hallucc": { "type": "http", "url": "http://127.0.0.1:8787/mcp", "headers": { "Authorization": "Bearer <your HallucC API key>" } } }}npx @modelcontextprotocol/inspector# choose Streamable HTTP, URL http://localhost:8787/mcp# add Custom Header: Authorization: Bearer <key>src/ server.ts Express + StreamableHTTP transport (stateless) + auth middleware + tool registration context.ts config loading + API key extraction backend.ts BackendClient (key pass-through, unified 401/429/5xx mapping) + toMcpResult schemas.ts zod input schemas for the 5 tools (aligned with backend Pydantic Fields) tools/ verifyText.ts → /detect verifyAgent.ts → /detect-agent checkCuaActions.ts → /cua/classify checkCuaCodeAudit.ts → /cua/audit-code checkSafety.ts → /guard/check (fast → /guard/check-fast) index.ts registerAllTools