MCP 服务器

InterOrdra MCP

A semantic gap detection tool that identifies miscommunication and misalignment between texts by measuring semantic distance using embeddings. It enables AI agents to analyze conversation sequences for conceptual drift and reframe questions to uncover hidden needs.

README

title: InterOrdra MCP emoji: 🔍 colorFrom: purple colorTo: blue sdk: docker pinned: false

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InterOrdra MCP Server

Semantic gap detection tool for AI agents.

InterOrdra detects when two systems are talking without listening to each other — measuring the semantic distance between texts and surfacing the invisible disconnections that cause miscommunication, misalignment, and failed coordination.

Built as an MCP server so any agent can use it.

Requirements

Python 3.10+
ANTHROPIC_API_KEY environment variable set with your own key

pip install fastmcp anthropic

Note: InterOrdra uses your own Anthropic API key. The author does not pay for your usage.

Tools

`detectar_gap`

Detects semantic gaps between two texts using real embeddings (Voyage AI via Anthropic). Returns a gap score, severity level, and vocabulary unique to each text.

{
  "texto_a": "the server is not responding to network requests",
  "texto_b": "I need the team to understand my product vision"
}

Returns:

{
  "gap_score": 0.94,
  "nivel": "alto",
  "mensaje": "Gap semántico significativo. Los textos hablan de mundos distintos.",
  "similaridad_semantica": 0.06,
  "palabras_solo_en_A": ["servidor", "red", "solicitudes"],
  "palabras_solo_en_B": ["visión", "producto", "equipo"],
  "metodo": "embeddings"
}

`reformular_pregunta`

Takes a question and generates three alternative framings using Claude to surface the real need behind it. Based on the Question Reframe method.

{
  "pregunta": "why doesn't anyone understand me"
}

Returns:

{
  "pregunta_original": "why doesn't anyone understand me",
  "variantes": [
    "What specific communication breakdown is happening in your current context?",
    "What would it look like if someone truly understood you — what would change?",
    "Which part of your message consistently gets lost or misinterpreted?"
  ],
  "instruccion": "Usa estas variantes para explorar el gap entre lo que se pregunta y lo que se necesita."
}

`analizar_conversacion`

Analyzes a sequence of messages to detect accumulating semantic gaps. Identifies where a conversation starts drifting apart.

{
  "mensajes": [
    "We need to improve system performance",
    "I think we should hire more engineers",
    "The budget for Q3 is already allocated",
    "Can we talk about team morale instead?"
  ]
}

Returns:

{
  "gaps_detectados": [
    {"entre_mensajes": "1 y 2", "gap_score": 0.45, "nivel": "medio"},
    {"entre_mensajes": "2 y 3", "gap_score": 0.71, "nivel": "alto"},
    {"entre_mensajes": "3 y 4", "gap_score": 0.83, "nivel": "alto"}
  ],
  "gap_promedio": 0.66,
  "punto_critico": {"entre_mensajes": "3 y 4", "gap_score": 0.83},
  "diagnostico": "Conversación gravemente desacoplada"
}

Connect to Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "interordra": {
      "command": "python",
      "args": ["/path/to/server.py"],
      "env": {
        "ANTHROPIC_API_KEY": "your-api-key-here"
      }
    }
  }
}

Replace /path/to/server.py with the actual path and add your own API key.

Restart Claude Desktop. InterOrdra will appear as an available tool.

Use cases

Detect misalignment between a question and its answer
Identify when two teams are operating in disconnected conceptual frameworks
Surface semantic gaps in multi-agent pipelines
Analyze conversations to find where the thread breaks
Reframe questions to uncover the real underlying need

Background

InterOrdra emerged from a pattern: seeing where two systems are broadcasting on completely different frequencies — technically communicating, actually disconnected.

The name comes from inter (between) + ordra (order/structure) — the space between ordered systems where gaps live.

Full project: github.com/rosibis-piedra/interordra