wikexa
Structured knowledge for AI agents — Wikipedia, Wikidata and Wiktionary as clean JSON. 1.9M searchable. Free, no auth.
Documentation
Wikexa
Structured knowledge for AI agents. Wikipedia, Wikidata and Wiktionary as
clean JSON instead of HTML. ~30x fewer tokens than fetching the page yourself.
- MCP endpoint: `https://wikexa.com/mcp`
- Registry: `com.wikexa/knowledge`
- Homepage: wikexa.com
- Agent guide: wikexa.com/agents
- Docs: wikexa.com/docs
- llms.txt: wikexa.com/llms.txt
Why
An agent fetching `en.wikipedia.org/wiki/Apple_Inc.` burns ~15,000 tokens of HTML
to recover ~500 tokens of facts. Wikipedia's own API returns wikitext, which is
barely better. One `lookup()` call here returns the facts directly.
Tools
| Tool | What it gives you |
|---|---|
| `lookup(entity, corpus?)` | Structured facts + ~200-token summary. Resolves aliases and Q-ids. |
| `article(title, sections?, max_chars?, corpus?)` | Full article as structured JSON — sections as an array, infobox as key/value. No HTML or wikitext. |
| `define(word, language?, pos?)` | Dictionary definitions from Wiktionary — 8.15M entries across ~4,000 languages. Grouped by language, with etymology and pronunciation. |
| `search(query, limit?, corpus?)` | Ranked matches blending relevance, pageviews, and exact-title matching. Up to 50 results. |
| `recent(topic?, hours?, limit?)` | Recently changed articles — facts newer than your training cutoff. |
Every tool is also a REST endpoint backed by the same handler:
GET https://wikexa.com/v1/lookup?entity=Tim%20Cook
GET https://wikexa.com/v1/article?title=Apple%20Inc.§ions=History
GET https://wikexa.com/v1/define?word=serendipity&language=English
GET https://wikexa.com/v1/search?query=quantum%20computing&limit=5
GET https://wikexa.com/v1/recent?topic=electionExample
curl -s 'https://wikexa.com/v1/lookup?entity=Tim%20Cook'{
"title": "Tim Cook",
"wikidata_id": "Q265852",
"description": "American business executive (born 1960)",
"summary": "Timothy Donald Cook is an American business executive...",
"infobox": { "born": "1960-11-01", "education": "Auburn University; Duke University", "title": "CEO of Apple Inc." },
"facts": { "occupation": "business executive", "employer": "Apple Inc.", "citizenship": "United States" },
"related": ["Apple Inc.", "Steve Jobs", "iPhone"],
"source_url": "https://en.wikipedia.org/wiki/Tim_Cook",
"license": "Wikipedia text CC BY-SA 4.0; Wikidata facts CC0"
}Connect
Claude Code / any MCP client:
claude mcp add --transport http wikexa https://wikexa.com/mcpCursor / VS Code (`mcp.json`):
{
"servers": {
"wikexa": {
"type": "http",
"url": "https://wikexa.com/mcp"
}
}
}Raw JSON-RPC:
curl -s -X POST https://wikexa.com/mcp \
-H 'content-type: application/json' \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call",
"params":{"name":"lookup","arguments":{"entity":"Apple Inc."}}}'Discovery
| Path | What it serves |
|---|---|
| `/.well-known/mcp.json` | MCP server metadata |
| `/.well-known/agent.json` | Agent card |
| `/openapi.json` | OpenAPI 3.1 spec |
| `/llms.txt` | Plain-text orientation for LLMs |
| `/.well-known/oauth-authorization-server` | Returns 404 — no auth required |
Coverage
- 476,616 encyclopedia articles (top by pageviews)
- 10.2M Wikidata entity records
- 8.15M Wiktionary dictionary entries (~4,000 languages)
- 194,870 records from Wikiquote, Wikibooks, Wikiversity, Wikivoyage
- 1.9M full-text searchable with pageview-weighted ranking
Performance
Served from the Cloudflare edge. 5–12ms warm with zero storage operations.
Verify with the `x-wikexa-ops` response header.
Pricing
Free for individuals and open-source projects. Commercial volume plans available
at wikexa.com.
Token control
`article()` takes `sections` and `max_chars`. Ask for the section you need
rather than the whole article. Empty fields are omitted from all responses to
minimize token usage.
Licensing
Wikipedia text is CC BY-SA 4.0 — every response carries `license` and
`source_url`. Wikidata facts are CC0. We add no restrictions on top of those
licences. Paid plans buy service capacity and support, never content rights.
Wikexa is not affiliated with the Wikimedia Foundation.
Frequently asked questions
What is wikexa?
wikexa is Structured knowledge for AI agents — Wikipedia, Wikidata and Wiktionary as clean JSON. 1.9M searchable. Free, no auth.
How do I install wikexa?
Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.
Is wikexa open source?
Yes — it is hosted on GitHub at https://github.com/nlapi/wikexa.
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