decompose-mcp 0.1.0

The missing cognitive primitive for AI agents. Structured intelligence from any text.

Decompose

Stop prompting. Start decomposing.

The missing cognitive primitive for AI agents. Decompose turns any text into classified, structured semantic units — instantly. No LLM. No setup. One function call.

---

Before: your agent reads this

The contractor shall provide all materials per ASTM C150-20. Maximum load
shall not exceed 500 psf per ASCE 7-22. Notice to proceed within 14 calendar
days of contract execution. Retainage of 10% applies to all payments.
For general background, the project is located in Denver, CO...

After: your agent reads this

[
  {
    "text": "The contractor shall provide all materials per ASTM C150-20.",
    "authority": "mandatory",
    "risk": "compliance",
    "type": "requirement",
    "irreducible": true,
    "attention": 8.0,
    "entities": ["ASTM C150-20"]
  },
  {
    "text": "Maximum load shall not exceed 500 psf per ASCE 7-22.",
    "authority": "prohibitive",
    "risk": "safety_critical",
    "type": "constraint",
    "irreducible": true,
    "attention": 10.0,
    "entities": ["ASCE 7-22"]
  }
]

Every unit classified. Every standard extracted. Every risk scored. Your agent knows what matters.

---

Install

pip install decompose-mcp

Use as MCP Server

Add to your agent's MCP config (Claude Code, OpenClaw, Cursor, etc.):

{
  "mcpServers": {
    "decompose": {
      "command": "uvx",
      "args": ["decompose-mcp", "--serve"]
    }
  }
}

Your agent gets two tools:

• decompose_text — decompose any text
• decompose_url — fetch a URL and decompose its content

Use as CLI

# Pipe text
cat spec.txt | decompose --pretty

# Inline
decompose --text "The contractor shall provide all materials per ASTM C150-20."

# Compact output (smaller JSON)
cat document.md | decompose --compact

Use as Library

from decompose import decompose

result = decompose("The contractor shall provide all materials per ASTM C150-20.")

for unit in result["units"]:
    print(f"[{unit['authority']}] [{unit['risk']}] {unit['text'][:60]}...")

---

What Each Field Means

Field	Values	What It Tells Your Agent
authority	mandatory, prohibitive, directive, permissive, conditional, informational	Is this a hard requirement or background?
risk	safety_critical, compliance, financial, contractual, advisory, informational	How much does this matter?
type	requirement, definition, reference, constraint, narrative, data	What kind of content is this?
irreducible	true/false	Must this be preserved verbatim?
attention	0.0 - 10.0	How much compute should the agent spend here?
entities	standards, codes, regulations	What formal references are cited?
actionable	true/false	Does someone need to do something?

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Why No LLM?

Decompose runs on pure regex and heuristics. No Ollama, no API key, no GPU, no inference cost.

This is intentional:

• Fast: <500ms for a 50-page spec
• Deterministic: Same input always produces same output
• Offline: Works air-gapped, on a plane, on CI
• Composable: Your agent's LLM reasons over the structured output — decompose handles the preprocessing

The LLM is what your agent uses. Decompose makes whatever model you're running work better.

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Built by Echology

Decompose is extracted from AECai, a document intelligence platform for Architecture, Engineering, and Construction firms. The classification patterns, entity extraction, and irreducibility detection are battle-tested against thousands of real AEC documents — specs, contracts, RFIs, inspection reports, pay applications.

License: Proprietary — Copyright (c) 2025-2026 Echology, Inc.

Philosophy: All intelligence begins with decomposition.