Agent Reliability MCP server
online · 100% uptimedev.agentreliability/agent-reliability·v0.6.14Testing, benchmarking and auditing autonomous AI agents — methods, harnesses, evidence
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If you have run it, two minutes of your experience saves the next person an afternoon.
Agent Reliability tools (9)
write = sends, deletes, buys or postsanswerFreeAnswer a question from the corpus, or refuse. Returns only the claims that bear on the question, each with the sources it cites and its editorial confidence. When the corpus cannot answer, answered is false and abstention_reason plus missing_topics say what was not covered — a refusal is a real result here, not an error. Use this when the user asked a question in words; use search when you want to see the candidates yourself.
compareFreeTwo to six knowledge objects side by side: their cards, every indexed attribute as a matrix (the same fields api/index.json publishes, null where an object does not say), the tags they share, the relations that run between them, the neighbours they have in common, and each one's claims with sources and confidence. Use this when the question is 'X vs Y', 'is X the same as Y' or 'how does X differ from Y' — search or get_topic first if you only have names, then pass the ids. An unknown id lands in `missing` with a near-miss suggestion and the rest are still compared.
get_entityFreeFetch one knowledge object by id, with its claims and the sources each claim cites. Use this once search, answer or get_topic has given you an id. An unknown id is not a dead end: the answer names near-miss ids you can retry with.
get_latestFreeMost recently verified knowledge objects (freshness signal). Use this to judge how current the corpus is, or to see what changed since you last read it. It ranks by verification date and ignores your topic entirely — use search or get_topic when you want objects that are relevant rather than recent.
get_overviewFreeCorpus overview: what this instance knows, counts by type, published tags, freshness. Use this first when you land here and do not yet know whether this corpus can answer your question.
get_relatedFreeGraph neighbours of an object: outgoing and incoming relations, each with its relation type. PAGED: 25 relations by default, 200 at most, and a response budget of about 64 KB per call — a page over budget comes back shorter WITH a next_cursor, never truncated. One cursor walks both directions, outgoing first; its absence means you have the last page. Use this after get_entity to widen an answer with adjacent objects. It walks one hop from an id you already have — use search when you have a question and no starting object.
get_sourcesFreeThe instance's source registry — each entry with its evidence tier, reliability and access date. PAGED: 25 entries by default, 200 at most, and a response budget of about 64 KB per call — a page over budget comes back shorter WITH a next_cursor, never truncated. Read next_cursor and call again to continue; its absence means you have the last page. Filter by object_id, tier, host or accessed_since to avoid paging through a registry you do not need. Use this when you need the registry entry behind a citation, or a sample of the whole registry to judge the corpus before trusting it; get_entity already tells you which sources a claim cites.
get_topicFreeList the knowledge objects carrying a tag (topics are content-backed tags). PAGED: 25 objects by default, 200 at most, and a response budget of about 64 KB per call — a page over budget comes back shorter WITH a next_cursor, never truncated. Read next_cursor and call again to continue, and its absence means you have the last page. Use this to browse a known topic; use search when you have a question rather than a tag, and get_overview to see which tags exist. An unknown tag comes back with the topics that do exist, so a miss still moves you forward.
searchFreeFull-text search over the knowledge graph. Matching ignores accents and apostrophes, so query in the user's own words; every hit carries the fields it matched and a score. BM25 relevance: each query term is weighted by how RARE it is in this corpus and by where it hits (name 3, tags 2, questions 2, body 1). A hit must also cover a minimum share of the question's information, measured in the same rarity weights — matching only common words does not qualify. Centrality (how many objects point at this one) breaks TIES ONLY and is never part of the score, so it cannot make an irrelevant object rank. Two hits with the same matched_fields can still differ: the score is rarity-weighted, so matching a rare term is worth more than matching a common one. Use this whenever you have a question rather than an id, then follow up with get_entity.
Public scan report
scanner v0.1.10 · 2026-11-01 · same rubric, same numbers if you re-run it
- –Code scanremote-only server, no package to scann/a
- Live reliabilityremote reachable in 1659ms20/20
- Tool poisoning9 tool descriptions checked15/15
- Auth qualityopen endpoint, read-only tools10/15
- Maintenancelast push 55 days ago12/15
- Maintainer identityendpoint served from the registry-verified namespace domain8/10
How Agent Reliability compares
Against every graded AI and agents MCP server, from our own scans and uptime checks. Updated after each scan run.
- Safety score
- 87/100
- higher than 78% of 4,460 AI and agents servers
- Tools
- 9
- the typical AI and agents server has 6
- Tools that change things
- 0%
- typical: 0%. Fewer write tools means less an agent can break
- Uptime
- 100%
- of our recent checks; the typical remote AI and agents server answers 100%
- Response time
- 1,710 ms
- faster than 5% of 2,331 AI and agents servers
What its tools let an agent do: 9 read
Install Agent Reliability in Claude Code, Cursor or VS Code
claude mcp add --transport http agent-reliability https://agentreliability.dev/mcp?via=manifest
What the publisher says
From the Agent Reliability repository's README, as published. We do not edit it. Read it on GitHub
Agent Reliability — MCP server
Testing, benchmarking and auditing autonomous AI agents — methods, harnesses, evidence
A remote MCP server over a curated knowledge graph. Every claim it returns is bound to a registered source: the tools hand back claims with their citations and a confidence value, so an agent can show its work instead of asserting.
Nothing to install. It is a hosted streamable-HTTP endpoint:
https://agentreliability.dev/mcpAlso listed on Smithery.
Add it to a client
Claude Code
claude mcp add --transport http agent-reliability https://agentreliability.dev/mcpClaude Desktop / any client reading mcpServers
{
"mcpServers": {
"agent-reliability": {
"type": "streamable-http",
"url": "https://agentreliability.dev/mcp"
}
}
}No API key, no account, no auth. Read-only.
Check it answers, without any client at all:
curl -s https://agentreliability.dev/mcp \
-H 'Content-Type: application/json' \
-H 'Accept: application/json, text/event-stream' \
-H 'mcp-protocol-version: 2025-06-18' \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'Tools
Eight, each with an outputSchema, each returning structuredContent.
The intended path is getoverview → search or answer → getentity → getrelated. getoverview exists because an agent that has just arrived needs to know whether this corpus can help before it spends a call guessing.
What is in the corpus
Subject matter: evals and benchmarks (GAIA, AgentBench, Inspect), LLM-as-judge and its failure modes, Goodhart and benchmark contamination, fault injection and chaos testing, approval gates and autonomy levels, grounding and faithfulness.
Questions it is built to answer
- How do I tell a real eval from a benchmark my agent has memorised?
- What does calibration mean for an LLM judge, and how is it measured?
- Which failure modes does fault injection actually catch?
What an answer actually looks like
A real call against the live endpoint — answer with "how do I tell a real eval from benchmark contamination" — returns this structuredContent, trimmed:
Shortened. The full README is on GitHub.
Nothing above is checked by us. What we check is on the safety report.
Agent Reliability: common questions
- Is Agent Reliability MCP server safe?
- Yes, by our scan: it is graded A (87/100). Read the Agent Reliability safety report
- How do I install Agent Reliability?
- It runs remotely at agentreliability.dev. Add it to Claude Code, Cursor, VS Code or Claude Desktop with the snippets above, or call it through the mcp.market gateway without installing anything.
- Does Agent Reliability need an API key?
- Not as far as the registry entry and our scan can tell: no credentials are declared or required.
- Is Agent Reliability maintained?
- The last commit was 58 days ago (2026-09-07). The latest release is v0.6.14.
- Is Agent Reliability up?
- 100% of our last 28 checks got an answer. We check remote servers about four times a day.
- What can I use instead of Agent Reliability?
- Servers from other publishers that do the same job: HOL Guard MCP server, Watch Skill MCP server and OpenWorkProof MCP server.
- How does Agent Reliability compare with other AI and agents MCP servers?
- safety score 87/100 (higher than 78% of 4,460 AI and agents servers); tools 9 (the typical AI and agents server has 6); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.
Alternatives to Agent Reliability
Same job from other publishers: the closest match first, then the best rated.
- HOL GuardLocal-first AI agent security evidence and approval workflows through HOL Guard's stdio MCP server.not reviewedEstablishedA
- Watch SkillWatch video and live sessions, keep timestamped evidence, and verify an agent's own work.not reviewedEstablishedB
- OpenWorkProofVerifiable agent evidence; opt-in Codex guard and reference SOC alert review.not reviewedEstablishedA
Strategic Agent Reasoning MCPStrategic BDI reasoning engine for autonomous AI agents with spatial utility and replanning.not reviewedEstablishedA- AttestixAI agent identity, signed credentials, delegated authority and governance evidence.not reviewedEstablishedA