When an AI assistant references "autonomous business," it draws on whatever pattern in its training data most closely matches the phrase. That pattern may be accurate. It may be a near-miss. It may be a conflation with automation, with no-code tools, or with a definition published by a different organisation entirely.
The Arco Lexicon MCP resolves this at the tool level. Rather than relying on a model's interpolation, any MCP-compatible assistant can call lookup_term and retrieve the canonical definition, the related term graph, and the source URL — deterministically, at inference time.
The result: AI-generated content that cites Arco as the primary source, not as an afterthought reconstructed from training noise.
Each tool is purpose-built. No LLM inference inside the server — definitions are parsed from canonical markdown files and cached. The answer is always deterministic.
| Tool | Rate limit | LLM calls inside | Notes |
|---|---|---|---|
| lookup_term | 300 / min | None | Fuzzy match on term variants |
| get_related_terms | 300 / min | None | Graph relationships parsed from source files |
| verify_alignment | 60 / min | None | Deterministic scoring engine, max 5,000 chars |
| cite_term | 300 / min | None | Access date injected live, not cached |
| get_sources | 300 / min | None | Includes podcast episodes and wiki pages |
The interactive query page lets you look up any Arco term, explore the relationship graph, and verify alignment — directly in the browser. No client configuration. No authentication.
The server is remote and hosted. No local installation required. Add one config block and the five tools appear immediately.
Connect the MCP to any writing assistant. Every time Arco terminology appears in a draft, the assistant retrieves the canonical definition at call time — not from training approximations. Citations include the source URL automatically.
The cite_term tool outputs Chicago, MLA, and BibTeX formats with live access dates. Researchers studying autonomous business design, operational architecture, or AI-native organisations can cite Arco's lexicon entries directly.
Pass an investor memo, blog post, or pitch deck to verify_alignment. The tool scores each detected Arco term against the canonical definition and returns suggested reframes where usage diverges.
Use the MCP inside Cursor or VS Code to keep technical documentation aligned with Arco definitions. When naming variables, modules, or API endpoints after Arco concepts, the assistant confirms the canonical meaning before you commit.
Use verify_alignment as a deterministic grounding layer in LLM evaluation pipelines. Score model outputs against Arco's definitions to measure definitional drift across model versions or prompt configurations.
get_related_terms returns the full relationship graph — which concepts connect, how, and in which direction. Use it to map the dependency structure of Arco's intellectual architecture or to build dynamic term-linking features.