by neuronto
Neuronto Agentic Resource Discovery (ARD) Index. Federated search across every public ARD registry, plus a verified tool index read from each MCP server's own tools/list, hybrid lexical and semantic retrieval, and ARD-Bench.
# Add to your Claude Code skills
git clone https://github.com/neuronto/agentic-resource-discoveryGuides for using ai agents skills like agentic-resource-discovery.
agentic-resource-discovery is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by neuronto. Neuronto Agentic Resource Discovery (ARD) Index. Federated search across every public ARD registry, plus a verified tool index read from each MCP server's own tools/list, hybrid lexical and semantic retrieval, and ARD-Bench. It has 50 GitHub stars.
agentic-resource-discovery's catalog security scan is still queued. You can run an instant dependency and prompt-injection check now with the "Scan for vulnerabilities" button above.
Clone the repository with "git clone https://github.com/neuronto/agentic-resource-discovery" and add it to your Claude Code skills directory (see the Installation section above).
agentic-resource-discovery is primarily written in HTML. It is open-source under neuronto on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh agentic-resource-discovery against similar tools.
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One search across every public ARD registry, plus a verified index of what MCP servers actually expose.
neuronto.com · API · Submit your server · Benchmark · Dataset · Manifest
ARD is short for Agentic Resource Discovery, an open specification for how AI agents find the tools, skills, agents and APIs they need, published in June 2026 by a working group including Google, Microsoft, Hugging Face, AWS, Cisco, GitHub, Nvidia, Salesforce and Snowflake.
An agentic resource is anything an AI client can call to get work done: an MCP server, an A2A agent, a skill, an API, a workflow.
ARD answers one question, "what is available for this task?", and then gets out of the way. It is not a runtime and does not replace MCP or A2A. It tells an agent what exists; the agent connects using the resource's own protocol.
Today an agent can only use capabilities someone installed for it in advance. Every tool has to be wired in by hand, and every tool description has to sit in the context window, competing for space with the actual work. That model does not survive contact with an ecosystem of thousands of tools, let alone millions.
ARD moves the selection problem out of the context window and into a search service, the same shift the early web made when it went from curated link directories to search engines.
For that to work, two sides have to exist. Publishers describe what they offer at a well-known location on their own domain. Registries index those descriptions and answer queries. Neuronto is both.
The specification defines three federation modes and makes auto the default: a
registry queries its peers, merges their results, and returns one set.
In practice each public registry answers only from its own catalogue, so the same question asked in four places returns four different answers and the client has to pick a side. That is the problem Neuronto exists to remove.
Ask Neuronto once and the query fans out across every public ARD registry concurrently. Results are fused with reciprocal rank fusion, which combines the orderings rather than the scores, necessary because each registry calibrates differently, and importing another service's scoring would import its biases with it.
The response says which registries answered and which timed out, so a caller always knows how much of the federation is behind an answer.
Federated by default. federation: auto implemented as specified: concurrent
fan-out under a hard time budget, fused ranking, per-upstream reporting. A slow peer
costs the budget and nothing more.
Complete conformance. Passes the specification's official conformance tool as
both a registry and a publisher with zero errors and zero warnings, including the
optional GET /agents listing as a properly paginated object.
Type normalisation. Three media types for MCP servers are in circulation
(application/mcp-server, application/mcp-server+json,
application/mcp-server-card+json) and two URN prefixes appear as discovery
identifiers (urn:air: and urn:ai:). Because filters match exactly, entries get
dropped silently. Neuronto normalises both on ingest, so a filter for MCP servers
returns them however the publisher spelled the type.
A verified tool index, not just a server index. Every other registry stores a server
name and whatever prose its publisher wrote. Neuronto handshakes with each indexed MCP
endpoint and reads its tools/list, so the index holds the real tool names and input
schemas, the thing an agent actually has to match on. Currently 32,183 verified tools
across 2,223 servers, plus 1,918 endpoints recorded as requiring credentials, which
no other registry reports. Introspection is read only: a tool is never called.
Hybrid retrieval. Sparse BM25 and dense vectors, fused with the same reciprocal rank fusion used for federation, so one query runs lexical, semantic and federated retrieval and returns a single ordering. The dense leg rides inside the federation budget and contributes nothing if it is unavailable, so the lexical fast path is never slowed by it.
Verified liveness. Indexed endpoints are probed and non-responding ones demoted in ranking. Registries built on self-published manifests accumulate dead links quickly; serving them is the fastest way to become the index nobody trusts. Entries are demoted rather than deleted, because services come back.
Manifests generated from evidence, not from a form. Most domains will never author a
manifest by hand. They already run an MCP server, or serve an OpenAPI document, or publish
llms.txt, and the manifest is a restatement of things a crawler can already find. Neuronto
probes a domain, emits an entry only for each resource that actually answered, records what
proved it, and hosts the result. Nothing is inferred, because a generated manifest that
guesses would put a claim on somebody's domain that they never made and cannot defend.
A private half of the index. The list of internal services an organisation's own agents may call usually lives in a system prompt, where nothing can search it and nobody can audit it. A domain that proves ownership by DNS can register those services, and one query then returns internal and public results together, each labelled with which it is. Private entries are held in separate storage from the public index rather than behind a flag, so no public search, count or page can reach them by construction.
Ranking that separates. A relevance score is only useful if the gap between the first and fifth result is legible. Scores are scaled to preserve real separation instead of compressing everything into a narrow band.
Search this index and the whole federation in one call:
curl -s https://neuronto.com/search \
-H 'content-type: application/json' \
-d '{"query":{"text":"scrape a website behind cloudflare"},"federation":"auto"}'
Or install it as an MCP server, so an agent searches from the interface it already speaks:
claude mcp add --transport http neuronto https://neuronto.com/mcp
| Endpoint | Purpose |
|---|---|
POST /search |
Ranked results. federation: auto (default), referrals, none. |
POST /explore |
Facet counts over the index. |
GET /agents |
Deterministic paginated listing, for browsing rather than ranking. |
POST /mcp |
Search, tool search, index statistics and publishing, as MCP tools. |
POST /tools, GET /tools?q= |
Tool level search over verified tools rather than servers. |
POST /submit |
Index an MCP endpoint or a manifest-publishing domain. |
POST /audit |
Publishing report: discovery, conformance, coverage, competition. |
POST /manifest/build |
Generate a manifest for a domain from resources fetched there. |
GET /m/{host}.json |
That generated manifest, hosted. |
POST /claim, POST /claim/verify |
Prove domain ownership by DNS TXT, receive a key. |
POST /private/entries |
Register internal services. Key required. |
GET /bench, GET /adoption |
Retrieval measurement, and who publishes a manifest. |
GET /.well-known/ard.json |
Our own publisher manifest. |
GET /openapi.json |
OpenAPI 3.1 for everything above. |
Every top result scores near 100. That is deliberate: the score is relative to the best hit
in its own result set, because BM25 magnitudes are corpus and query dependent, so an
absolute scale would mean nothing. It ranks well and, on its own, it misleads. The query
zzzz nonexistent capability qqqq scores 100, because something always comes first.
So every search response carries one absolute number beside the relative ones:
"queryMatch": {
"coverage": 0.0,
"confidence": "none",
"matchedTerms": [],
"queryTerms": ["zzzz", "nonexistent", "capability", "qqqq"],
"note": "each result's `score` is relative to the best hit in this response ..."
}
coverage is the fraction of the query's content words that the top result's own text
accounts for. It is corpus independent, which is the property the score cannot have, so it
separates "the best of several good answers" from "the best of nothing".
It measures overlap, not correctness. A query whose every word appears in an entry that does the opposite thing still scores 1.0. Treat it as a floor on confidence, never as a verdict, and never as a trust or safety rating.
No key and no signup for anything that reads the public index. A key exists only to admit a verified domain's own private entries, and is issued only against a DNS proof of ownership.
Relevance scores are semantic only and are never a trust, compliance or safety rating, the specification is explicit that trust evaluation is decoupled from discovery.
When you already know the shape of the call you need, the server hosting it is an implementation detail:
curl -s 'https://neuronto.com/tools?q=extract+text+from+a+pdf&limit=5'
Every tool returned was read from that server's own tools/list. T