Neuronto Agentic Resource Discovery (ARD) Index

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

What is ARD?

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.

Related MCP server: sage-mcp

The problem it solves

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.

Why a federated index

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.

What it does differently

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.

Where it fits

• Agent builders, stop hard-coding integrations. Ask for a capability at runtime and connect to whatever currently serves it best.

• API and tool vendors, publish one manifest on your own domain and become discoverable to every ARD client, without applying to a curated marketplace.

• Platform teams, run discovery over internal services so agents inside the organisation find them the same way they find public ones.

Using it

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

Registry API

Knowing when the answer is weak

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.

Searching tools instead of servers

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. The same search is available to agents as the MCP tool find_tool, alongside find_resource, registry_stats and publish_resource. Only publish_resource writes, and it is the only one declaring readOnlyHint: false, so a client can tell from the tool list alone which call has an effect.

Measuring whether any of this works

GET /bench publishes ARD-Bench, a head to head retrieval measurement across the public ARD registries. Ground truth is the publishers' own representativeQueries, so nothing is hand labelled, and the harness is app/bench.py in this repository.

The response separates two things that are easy to confuse: coverage, whether a registry indexes the target at all, and recall@k_when_carried, whether it retrieves the target when it does hold it. It also states its own known bias, and it reports the results that do not flatter us. In the current run, federated search scores slightly below lexical only and costs far more latency.

Who publishes an ARD manifest

GET /adoption tracks adoption of the specification itself: a named watchlist of organisations, and the manifest rate across every host the crawler has seen. At the time of writing, three of the twenty organisations on the watchlist publish a manifest: Hugging Face, Vercel and Zapier. All three serve it at /.well-known/ai-catalog.json, the path v0.91 renamed. Of 178 publishers our crawler has found, 157 serve the older ai-catalog.json and only 14 serve ard.json, which is why the tracker checks both: measuring the path rather than the practice gets the answer wrong.

The open dataset

The verified tool corpus is published as an open dataset, CC BY 4.0: huggingface.co/datasets/AgenticResourceDiscovery/verified-mcp-tools

tools.jsonl carries all 31,411 verified tools with their input schemas, servers.jsonl carries 7,708 introspection results including the auth requirement and failure kind. It exists because tool-retrieval research (ToolRet, ACL Findings 2025) has been benchmarked on assembled corpora rather than the live ecosystem, and this is the live ecosystem.

The badge

If your MCP server is in the index, a badge states what we verified: how many tools your server returned to tools/list, and whether the endpoint answers.

[![Neuronto verified tools](https://neuronto.com/badge/your.publisher.id.svg)](https://neuronto.com/console?domain=your.publisher.id)

The publisher id is the publisher segment of your URN, or your domain. The badge is a statement about what was observed, never a trust, safety or quality rating. Not indexed yet? Publish a manifest and the crawler will find you, or run the console audit.

Publishing your own resources

Four ways in, in ascending order of effort. There is no allowlist and no signup for any of them.

You already run an MCP server. Submit the endpoint. Neuronto completes an initialize handshake and reads the server's own tools/list, which is stronger evidence than a manifest claim because the server answered for itself.

curl -X POST https://neuronto.com/submit \
  -H 'content-type: application/json' \
  -d '{"endpoint":"https://example.com/mcp"}'

You are working inside an agent. The same thing as an MCP tool, so a resource can be listed from inside a conversation without leaving it.

{"method":"tools/call","params":{"name":"publish_resource",
 "arguments":{"endpoint":"https://example.com/mcp"}}}

It verifies rather than trusts, exactly as the HTTP route does, and calls that route rather than reimplementing it so the two cannot drift apart.

You have no manifest and do not want to write one. Ask for one to be generated from what your domain already exposes, and either copy it or link it.

curl -X POST https://neuronto.com/manifest/build \
  -H 'content-type: application/json' -d '{"domain":"example.com"}'

Only resources that actually answered become entries, and each carries the evidence that produced it. The hosted copy at https://neuronto.com/m/example.com.json says in its own response headers that it was generated rather than authored by the domain owner.

You have a manifest. Serve it at /.well-known/ard.json and submit the domain, or wait for the crawler.

curl -X POST https://neuronto.com/submit \
  -H 'content-type: application/json' -d '{"domain":"example.com"}'

Serve it at /.well-known/ai-catalog.json as well. Version 0.91 of the specification renamed the file, but the deployed base has not moved: of the ARD publishers verified so far, the large majority still serve only the older path, so a consumer that checks one name misses most of the ecosystem.

Include representativeQueries on every entry. It is the term registries build their semantic index from, and an entry without it is a valid catalogue entry that no search will ever return.

Checking whether it worked

curl -X POST https://neuronto.com/audit \
  -H 'content-type: application/json' -d '{"domain":"example.com"}'

Reports whether the manifest is reachable on each of the four discovery paths, whether it satisfies the specification entry by entry, which registries actually return you, and who is returned instead of you for the queries you asked to be found for, with what those entries have that you may not. Free, no signup. There is a browser version at /console.

Private entries

An organisation can register the internal services its own agents may call, and search across public and internal resources in one query.

# 1. ask for the proof record, publish it as a TXT record at your apex
curl -X POST https://neuronto.com/claim \
  -H 'content-type: application/json' -d '{"domain":"example.com"}'

# 2. verify, which returns an API key
curl -X POST https://neuronto.com/claim/verify \
  -H 'content-type: application/json' -d '{"domain":"example.com"}'

# 3. register an internal service
curl -X POST https://neuronto.com/private/entries \
  -H "authorization: Bearer $KEY" -H 'content-type: application/json' \
  -d '{"entry":{"displayName":"Staff Directory","url":"https://internal/mcp",
       "description":"Look up an employee record by name or badge number.",
       "representativeQueries":["look up an employee record"]}}'

# 4. the same key on search admits them, alongside public results
curl -X POST https://neuronto.com/search \
  -H "authorization: Bearer $KEY" -H 'content-type: application/json' \
  -d '{"query":{"text":"look up an employee record"}}'

The proof value is derived from the domain and never changes, so asking again does not invalidate a record already published. It is read over DNS over HTTPS, so it verifies as soon as the authoritative zone serves it. Verification is the only thing that issues a key.

Every result says whether it came from the public index or from your own entries. Private entries are never ranked against public ones by corpus statistics, because a single tenant's index is too small for those statistics to mean anything; they are placed by how much of the query their own text accounts for, which means the same thing at any size.

Specification

• Agentic Resource Discovery, v0.91

• ards-project/ard-spec

Licence

Apache-2.0