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Concordance Engine MCP Server

@matharrismma

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stdio

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matharrismma

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matharrismma

关于 Concordance Engine MCP Server

O(1) authority-based validation across seven domains (chemistry, physics, mathematics, statistics, computer science, biology, governance). Replaces O(n²) consensus coordination. Four-gate pipeline: RED, FLOOR, BROTHERS, GOD. MCP server included — connects to Claude Desktop and Cl

Concordance Engine MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "concordance-engine": {
      "command": "concordance-mcp"
    }
  }
}

Concordance Engine MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Concordance Engine?

Concordance Engine is a Python validation engine and MCP server that checks decision packets and computational claims against fixed external authorities (conserved laws, proven mathematics, pre‑registered statistical methods) rather than polling internal consensus. It implements O(1) validation, halting at the first gate failure, and never self‑confirms. Designed for AI systems, researchers, and governance workflows.

How to use Concordance Engine?

Install with pip install -e ".[mcp]" then run concordance-mcp to start the MCP server. Configure in Claude Desktop or add via claude mcp add. Alternatively, use the CLI: concordance validate <packet.json>. MCP tools return {"status":"ERROR",…} on bad input, making them safe inside LLM tool loops.

Key features of Concordance Engine

  • O(1) external authority validation (replaces O(n²) consensus).
  • Eleven computational verifiers (chemistry, physics, math, statistics, CS, biology, governance).
  • Four‑gate pipeline (RED, FLOOR, BROTHERS, GOD) with deterministic halting.
  • Safe for LLM loops: tools never raise exceptions.
  • MCP integration with Claude Desktop and Claude Code.
  • CLI with summary/verbose/json output.

Use cases of Concordance Engine

  • Validate governance decision packets for structural completeness and witness consistency.
  • Verify chemistry equation balance, physics dimensional analysis, and conservation laws.
  • Recompute p‑values and multiple‑comparison corrections from raw statistical inputs.
  • Check computer‑science code for termination, functional correctness, and runtime complexity.
  • Enforce biological experiment validity (replicates, dose‑response, power analysis).

常见问题

1

How is Concordance Engine different from consensus‑based validation?

Consensus‑based validation scales O(n²) and depends on the least reliable participant. Concordance Engine validates every claim against fixed external standards, scaling O(1) independent of participant count.

2

What dependencies are required?

Required: `sympy>=1.12`, `numpy>=1.26`, `scipy>=1.11`. Optional: `jsonschema>=4.21.0` (full schema validation), `mcp>=1.0.0` (MCP server).

3

How do verifiers handle invalid input?

Each verifier returns a status (`CONFIRMED`, `MISMATCH`, `ERROR`, `NOT_APPLICABLE`) with a human‑readable `detail` string and structured `data`. They never raise exceptions.

4

Can I add custom verifiers or domains?

Yes. Add a domain validator in `domains/<domain>.py` exposing `validate_red(packet)` and `validate_floor(packet)`, or add a computational verifier in `verifiers/<domain>.py` with a `run(packet)` function and register it in `verifiers/__init__.py`.

5

What are the four gates?

RED (hard, attestation + computational verification → REJECT), FLOOR (hard, structural rules → REJECT), BROTHERS (soft, witness count → QUARANTINE), GOD (soft, elapsed wait → QUARANTINE). The engine halts at the first gate failure.

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