Agent Ready
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| AGENT_READY_API_KEY | Yes | Bearer token issued from the Agent Ready dashboard. | |
| AGENT_READY_API_URL | No | Override for self-hosted or staging deployments. | https://agent-ready.dev |
| AGENT_READY_GET_TIMEOUT_MS | No | Timeout for get_scan and per-poll fetches. | 5000 |
| AGENT_READY_SCAN_TIMEOUT_MS | No | How long scan_site polls before returning a running placeholder. | 60000 |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| prompts | {
"listChanged": true
} |
| resources | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| scan_siteA | Runs the agent-ready.dev scanner against a URL and returns structured results: Vercel score, llmstxt.org score, and per-check findings with remediation hints. Works without an API key on the anonymous free tier (3 scans/30 days per IP, 25-page depth, synchronous). With a Pro AGENT_READY_API_KEY it scans deeper (up to 250 pages) and may take up to ~60s; if the local poll deadline elapses, the tool returns the scan id and asks you to poll with get_scan. |
| get_scanA | Fetches a completed or in-progress scan by its id. Requires a Pro API key — scan history is account-scoped. (Anonymous scan_site calls return their result inline, so keyless use never needs this tool.) |
| askA | Natural-language search (NLWeb /ask) over Agent Ready's own content — scoring methodology, the check registry, the specs it validates, and the content library (explainers, comparisons, how-to guides, glossary). Public, no API key required. Returns Schema.org-typed result objects; optional itemType narrows to a corpus type and mode 'summarize' adds an extractive summary. |
| validate_structured_dataA | Validates a page's (or a pasted) JSON-LD against Agent Ready's structured-data checks (schema lint + agent-coherence: freshness honesty, canonical/.md coherence, entity-name consistency, extraction signal) and returns a verdict with per-check fix guidance. Provide exactly one of |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| scan | Run a fresh agent-readability scan against a URL and summarise the most important findings. |
| interpret_scan | Fetch a previous scan by id and translate the per-check findings into plain-English explanations. |
| remediation_plan | Fetch a scan by id and produce a prioritised, actionable remediation plan, optionally focused on SEO or agent-protocol fixes. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| methodology | How Agent Ready computes the 0–100 readability score and the llms.txt sub-score. Covers the 71 checks across four categories, rating bands, weighting, and JS-rendering handling. |
| checks | Reference table of all 71 checks Agent Ready runs, grouped by category (site, page, llms.txt, protocol), plus the 23-check accessibility suite scored as a separate accessibility sub-score. Each row pairs the stable check ID (e.g. P11, S15, L9, C3, A7) with its human-readable name. Use this to identify a check by id when interpreting scan results. |
| llms-txt | The /llms.txt file agent-ready.dev publishes for AI agents discovering it as a tool. Mirrors the live document at https://agent-ready.dev/llms.txt. Useful as a worked example for the llms.txt validator and for clients introspecting Agent Ready's surface. |
| specs | Canonical URLs and check-ID mappings for the specifications Agent Ready implements: Vercel Agent Readability Spec, llmstxt.org, MCP Server Cards (SEP-1649 / RFC 9728), A2A Agent Cards (a2a.proto v1.0.0), Wildcard agents.json, agent-permissions.json, UCP (RFC 8414), x402 and MPP payments, NLWeb, API Catalog (RFC 9727), Web Bot Auth, Agent Skills Discovery, content parity, and Agent-driven UI (A2UI). |
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose: scanning a site, retrieving scan results, searching documentation, and validating structured data. No overlap or ambiguity.
All tool names follow a consistent verb_noun snake_case pattern. 'ask' is a concise verb, but fits as it is a direct action.
Four tools are well-scoped for Agent Ready's domain: scanning, result retrieval, knowledge base search, and validation. Not too few or too many.
The tool surface covers the core workflows: scan execution, result polling, documentation lookup, and structured data validation. No obvious gaps for the stated purpose.