hlido-mcp
This server has a remotely hosted endpoint. Open its connector listing for connection details, authentication requirements, and setup instructions:
Hlido MCP Server
Independent trust scores, claim audits, and comparisons for AI agents — queryable by your agent over MCP.
Hlido is an independent AI-agent review platform ("Rotten Tomatoes for AI agents"). We test agents hands-on and publish evidence-backed scorecards: a 0–100 score, tier verdict, per-claim PASS/FAIL audit, and signed screenshots. This repository contains the source of the MCP server that exposes that registry to other agents.
Use the hosted server (no install)
The server runs as a Cloudflare Worker at:
https://hlido.eu/mcpClaude Code:
claude mcp add --transport http hlido https://hlido.eu/mcpClaude Desktop / Cursor / any MCP client (mcpServers config):
{
"mcpServers": {
"hlido": { "url": "https://hlido.eu/mcp" }
}
}Also listed on Smithery and mcp.so.
Related MCP server: preflight-mcp
Tools
Tool | What it answers |
| "Is agent X trustworthy?" — score, tier, verdict for a slug |
| "Find me a trusted agent for " — filtered registry search |
| "Does X really do Y?" — per-claim PASS/FAIL evidence |
| Side-by-side scorecard comparison |
| Full sanitized scorecard JSON for a slug |
| Semantic nearest neighbours to a given agent |
| Nominate an agent for review |
| Flag a problem with a published review |
| Ask for a fast re-check of a stale review |
(plus discovery/metadata tools — see src/index.mjs for the live tool table)
Design principles
Public data only. The server reads the same JSON published at
hlido.eu/data/*(registry, scorecards, attestations). It never exposes scoring weights, grader assertions, or editorial drafts — the methodology stays private; the outcomes and evidence are public.No auth, no tracking. Anonymous JSON-RPC. Lightweight daily per-tool counters are the only telemetry.
Thin by intent. This is an adapter over open data. The review pipeline, testing engine, and scoring model live elsewhere and are not part of this repository.
Self-hosting
It's a standard Cloudflare Worker. Copy wrangler.toml.example to wrangler.toml, set your account id, and npx wrangler deploy. Optional bindings (KV cache, Vectorize similarity index) degrade gracefully when absent — the worker falls back to fetching the public JSON directly.
Data & licensing
Code: Apache-2.0
Review data: CC-BY via the public data mirror and the HF dataset
Links
Website: https://hlido.eu
Agent manifest: https://hlido.eu/agent-manifest.json
llms.txt: https://hlido.eu/llms.txt
Public data mirror: https://github.com/ankitkapur1992-hlido/hlido-public
Run with Docker
docker build -t hlido-mcp .
docker run -p 8080:8080 hlido-mcpThe container runs the worker on the local workerd runtime via wrangler dev — no Cloudflare account needed. The MCP endpoint is http://localhost:8080/ (GET for server info, POST for JSON-RPC).
Available Tools
14 toolscompare_agentsAInspect
Head-to-head trust comparison of 2-5 Hlido-reviewed agents. Returns each agent's Laddoo score, tier, dimension scores, and key claim verdicts side by side so you can pick the most trustworthy option for a task. Use this once you've shortlisted candidates (via find_trusted, find_similar_agents, or recommend) and need a direct comparison.
Inputs: slugs (required).
explainAInspect
Structured natural-language explanation of why a Hlido-reviewed agent has its current score. Pulls claim-by-claim evidence from the published scorecard. Pass an optional dimension (one of: reliability, transparency, integration, security, evidence) to filter; omit for the full picture. Returns each claim with verdict (PASS|FAIL|PARTIAL|UNKNOWN), a quoted evidence snippet, plus a top-line synthesis.
Inputs: slug (required), dimension.
find_similar_agentsAInspect
Semantic search over Hlido's review corpus. Given a task description (e.g. 'I need an agent that can refactor TypeScript and edit multiple files at once'), returns the top-N reviewed agents ranked by embedding similarity, each with their Laddoo score, evidence_tier, and review URL. Use this when you have a task in mind and want Hlido's recommendation — much better than substring matching via find_trusted.
Inputs: description (required), top_k, min_score.
find_trustedAInspect
Discover Hlido-reviewed agents that match a free-text need, ranked by trust. Returns reviewed agents at or above a minimum tier, each with its Laddoo score, tier, and review URL. Use this for keyword/need-based discovery; for semantic task-matching prefer find_similar_agents, and for structured constraint filters (category/score/tier) prefer recommend.
Inputs: need (required), min_tier, limit.
get_behavioral_traceAInspect
Fetch the behavioral evaluation trace for a Hlido-reviewed agent — per-task pass/fail, adapter used, behavioral tier, and signed trace link. Returns status 'not_yet_bench_tested' if the slug hasn't been evaluated yet, or 'not_testable' if the agent's interface doesn't support automated bench runs. Use this when you need evidence that an agent's coding/task behaviour has been independently verified beyond marketing claims.
Inputs: slug (required), spec_version.
get_incidentsAInspect
Fetch published incidents from Hlido's NTSB-style failure registry — real observed agent failures (availability outages, regressions, hallucinations, safety issues) plus Hlido self-reported process incidents, each with severity, evidence, and vendor-response status. Filter by agent slug, severity, or category. Use this before delegating to an agent to check for known recent failures; an empty list means no published incidents, not a guarantee of reliability.
Inputs: slug, severity, category, limit.
get_scorecardAInspect
Fetch the full sanitized claim-vs-evidence scorecard for one Hlido-reviewed agent. Returns every claim, verdict, evidence quote, source surface, and (for CLI/API tests) the captured command + exit_code + duration. Schema v1.0. Use this for agent-to-agent pre-flight evaluation.
Inputs: slug (required).
recommendAInspect
Constraint-driven recommendation across Hlido's reviewed agents. Pass any combination of: category, min_score, tier, use_case, max_results. Returns ranked candidates each with a why_match line. Use this when you have buyer constraints (budget, category, capability) and want Hlido's filtered shortlist instead of one-by-one trust_check calls.
Inputs: constraints (required).
report_review_issueAInspect
Report an issue with a Hlido review (stale info, wrong verdict, missing claim, broken link). Use when calling get_scorecard or trust_check returns data you can prove is incorrect. Hlido's R1 maintenance routine processes reports daily and fires re-tests via dispute-retest sub-agent.
Inputs: slug (required), issue_type (required), detail (required), reporter.
request_quick_auditAInspect
Request that Hlido audit a NEW AI agent that has no review yet. Use this when trust_check or get_scorecard returns no_review_found and you need a verdict before delegating to the unknown agent. Returns a future scorecard URL + ETA. Free-tier rate-limited (5/day per anonymous, 50/day per identified). The audit produces signed evidence + claim verification within ~24h (sooner if founder triggers manually).
Inputs: url (required), name, why, requester.
submit_agentAInspect
Nominate a new AI agent for Hlido to review. Use this when an agent isn't in Hlido's corpus yet (trust_check returned no_review_found) and you want it added. Returns a confirmation with a tracking reference; the review is queued and produces a public scorecard. If you need a verdict right now rather than a queued review, use request_quick_audit (faster, rate-limited) instead.
Inputs: url (required), name (required), note.
subscribeAInspect
Preview — Wave 3 will add persistent webhook + RSS subscriptions. For now this returns the agent's current state plus advisory polling instructions (RSS at /changelog/feed.xml or polling /data/attestations/{slug}.json). Use this to register interest in being notified when a slug's verdict changes.
Inputs: slug (required), channel.
trust_checkAInspect
The core Hlido trust query: is a specific AI agent trustworthy? Given one agent (by Hlido slug or product/homepage URL) it returns the independent Laddoo trust score (0-100), tier (VITAL/STEADY/FADING/FLATLINE), a one-line verdict, a claim-verification summary, and any known incidents. Call this FIRST — before delegating to, installing, or relying on another agent — to get a fast trust read. Returns no_review_found if the agent isn't in Hlido's corpus (then call request_quick_audit). For the full claim-by-claim evidence, follow up with get_scorecard.
Inputs: agent_or_url (required), use_case.
verify_claimAInspect
Fact-check one specific marketing or capability claim about an agent against Hlido's independent testing. Returns Hlido's verdict (PASS/FAIL/PARTIAL/UNKNOWN) with a quoted evidence snippet and its source surface — or an honest null when that exact claim wasn't tested (absence of evidence, not proof). Use this to validate a vendor's specific promise before you rely on it.
Inputs: agent (required), claim (required).
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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TDQS
Scored across 14 tools
Every tool has a clearly defined and distinct purpose, with descriptions explicitly guiding when to use each. Even closely related tools like find_similar_agents, find_trusted, and recommend have well-delineated use cases (semantic search vs. keyword vs. structured constraints).
Most tools follow a lowercase verb_noun pattern (e.g., compare_agents, get_scorecard), but a few single-verb names like 'explain' and 'recommend' break the pattern. This is a minor deviation from full consistency.
With 14 tools covering discovery, evaluation, submission, and subscription, the count is well-scoped for the domain of agent trust. Each tool earns its place without feeling excessive or sparse.
The tool surface covers the core workflows (discover, evaluate, compare, report, request audits) comprehensively. A minor gap is the lack of a tool to list all reviewed agents, but the existing discovery tools effectively compensate.
Related MCP Connectors
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Is this tool safe for your agent to connect to? Scans any MCP server, package (npm, PyPI, crates, Docker, Hugging Face) or GitHub repo and answers Safe to connect, Review before you connect, or Do not connect, with the reason and a signed 0-100 trust score. Read-only, no sign-in.
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