Thally


Your customers now ask AI tools before they open your docs. The Agent Layer publishes your documentation in the formats those tools read best, with the evidence to back every answer, so nothing gets guessed.

Ask like an agentWhat agents receive

llms.txt · MCP endpoint · structured JSON · source evidence

Trusted by the AI tools your readers already use

ClaudeCursorCopilotPerplexityGeminiv0Windsurf
QuestionMCPQ-114

What's the default request timeout?

search_docs called from inside the editor · 2m ago

LiveMCPS-201

MCP endpoint connected

4 tools, read-only: no scraping, no stale copies.

RetrievedGuides

/guides/long-running-jobs

evidence: bono@a1f9c2 · rank 2 of 3

RetrievedSDK

/sdk/configuration

evidence: bono@a1f9c2 · rank 1 of 3

AnswerCitedA-117

60 seconds before aborting

Grounded, never guessed · 2 sources

[1] /sdk/configuration · a1f9c2

[2] /guides/long-running-jobs

Freshness checked · 4m ago

Everything an AI tool needs to answer accurately about your product, served from the same source your customers read.

/llms.txttext/plain
128 pages indexedone entry per page

1# Facts first, layout gone

2/sdk/configuration4.1 KB.md
3/sdk/errors2.7 KB.md
4/guides/long-running-jobs6.3 KB.md
5/api/tokens3.8 KB.md

6124 more pages

Regenerated on every product change4m ago

A compact index that fits an agent's context budget

Docs an agent can
actually read.

MCP endpointconnected

https://docs.yourproduct.com/api/mcp

search_docs(query, limit)

query your docs live, ranked by relevance

read_page(pageId)

pull the current page, cited by commit

list_pages()

the whole site map, returned as data

agent_readiness()

score how well the docs serve agents

4 tools discoveredread-only

Standard Model Context Protocol, inside the editor

Tools, not scraping.
search and read built in.

Structured JSON

Concept references and blocks as data, so pipelines and custom agents parse meaning, not markup.

application/json

Evidence links

Every fact traces to a commit and symbol in your product: the receipts behind each answer.

source refs

Freshness signals

Each surface carries when it last synced with the product, so agents can prefer current facts.

updated-at

Scoped access

Decide which surfaces are public to agents and which stay internal: granular, revocable, read-only.

per-surface

An agent guessing about your API is worse than no agent at all. The Agent Layer replaces plausible-sounding fiction with sourced fact.

Confidently wrong

  • Answers from training data months or years out of date.
  • Invents parameters and defaults that never existed.
  • No way to check where an answer came from.
  • Sounds equally sure whether it's right or hallucinating.
Ungrounded model

Sourced and current

  • Reads your live docs, regenerated on every product change.
  • Cites the exact page and commit behind each claim.
  • Says less when it knows less. No evidence, no assertion.
  • You control what's exposed and can revoke it anytime.
Through the Agent Layer

This is your documentation answering through the Agent Layer. Pick a question, then watch it retrieve from the graph, answer in plain terms, and show exactly where each fact came from.

jahce.thally.site/api/mcpConnected
Pick a question below. The Agent Layer will retrieve from your live docs and answer with sources.
Try asking:

Claude
Cursor
Copilot
Perplexity
Gemini
Windsurf

Turn on the Agent Layer and your documentation becomes an MCP endpoint and llms.txt feed: current, cited, and scoped exactly how you want.