mcp-rule-engine

mcp-rule-engine

Captures code modifications via AST analysis, generates reusable rules, and injects them into AI agent context with version audit and token-budgeted rule retrieval.

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MCP Rule Engine — Cognition Engine & Trust Governance Layer

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A production-grade MCP server that combines a cognition graph engine with a trusted governance layer. Provides intelligent code pattern matching, AST-level constraint validation, and auditable injection approval for AI agents.

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📢 Protocol Update: We have adopted Apache 2.0 licensing with a formal trademark policy. Read the announcement → <!-- /TEMP_BANNER -->


The Problem It Solves

AI Agents are powerful but chaotic. They generate code confidently, yet they lack a persistent cognition layer to remember project-specific patterns across sessions, and they lack a governance layer to enforce security boundaries on their own output. Without these, every agent session starts from zero — repeating the same mistakes, ignoring your team's conventions, and producing code that looks plausible but violates project invariants.

This engine fixes that. It gives agents a long-term graph memory of project patterns (what works, what's forbidden, what's idiomatic in this codebase) and a trusted approval workflow so every injection is reviewed, audited, and accountable.


Core Features

  • Cognition Graph Engine — Intent recognition, weighted graph traversal, and AST constraint solving for intelligent code analysis
  • Trust Governance — Three-tier knowledge base with injection approval workflow, TTL-based proposals, and audit logging
  • Universal Connectivity — Stdio (local) and Streamable HTTP (remote) transports with full MCP lifecycle support
  • Agent Hard Constraints — Output schema enforcement with `validationRequired` auto-validation; non-compliant agent responses intercepted
  • Hot Config Updates — Dynamic threshold tuning with expert mode authorization and version chain tracking

Architecture

```mermaid flowchart LR Agent["AI Agent (Cursor / Claude / Cline)"] MCP["MCP Server (stdio / HTTP)"] CV["Constraint Validator"] GT["Graph Traverser"] IA["Injection Approval"] FL["Feedback Loop"] DB[("SQLite / Prisma")]

Agent -->|tools/list → tools/call| MCP
MCP -->|cognition_validate| CV
MCP -->|cognition_query| GT
MCP -->|cognition_approve_injection| IA
MCP -->|cognition_feedback| FL
CV -->|parse + validate| GT
GT -->|weighted BFS| DB
IA -->|TTL proposal| DB
FL -->|update weights| DB
DB -->|graph data| GT

```


Quick Start

Prerequisites

  • Node.js >= 18
  • npm >= 9

Setup

```bash git clone <repo-url> && cd mcp-rule-engine npm install npx prisma db push npm run build ```

Start Server

```bash

Stdio mode (default)

node dist/index.js

HTTP mode

TRANSPORT=http PORT=3000 node dist/index.js ```


MCP Integration

Cursor

Add to `.cursor/mcp.json`:

```json { "mcpServers": { "cognition-engine": { "command": "node", "args": ["dist/index.js"], "env": { "DATABASE_URL": "file:./dev.db" } } } } ```

Claude Desktop

Add to `claude_desktop_config.json`:

```json { "mcpServers": { "cognition-engine": { "command": "node", "args": ["path/to/mcp-rule-engine/dist/index.js"], "env": { "DATABASE_URL": "file:./dev.db" } } } } ```

VS Code (GitHub Copilot Chat / VS Code MCP Extension)

Add to your VS Code settings (User `settings.json` or workspace `.vscode/mcp.json`):

```json { "mcp": { "servers": { "cognition-engine": { "type": "stdio", "command": "node", "args": ["dist/index.js"], "env": { "DATABASE_URL": "file:./dev.db" } } } } } ```

Cline / Roo Code (HTTP)

```json { "mcpServers": { "cognition-engine": { "url": "http://localhost:3000", "transport": "streamable-http" } } } ```


Trust Governance Protocol

Three-Tier Knowledge

Tier Scope Node Type Validation
Global Universal patterns NegativeConstraint = REJECT Hard block
Project Project conventions PositiveConstraint = WARN Soft warning
Reuse Cross-project patterns Intent + Heuristic Weight-based

Injection Proposal State Machine

```mermaid stateDiagram-v2 [] --> PENDING: cognition_query triggers implicit proposal PENDING --> APPROVED: cognition_approve_injection(proposalId, APPROVE) PENDING --> REJECTED: cognition_approve_injection(proposalId, REJECT) PENDING --> OVERRIDDEN: cognition_approve_injection(proposalId, OVERRIDE) PENDING --> EXPIRED: TTL = 5 min elapsed APPROVED --> []: Rules injected into graph REJECTED --> []: Proposal discarded OVERRIDDEN --> []: Force-injected (audit logged) EXPIRED --> [*]: -32602 Proposal Expired + retryable:true ```

Proposals are in-memory with a 5-minute TTL. Concurrent proposals for the same context hash return the existing proposal to prevent conflicts. Expired proposals return `-32602 Proposal Expired` with `retryable: true`.

Constraint Validation Dual-Mode

  • REJECT (Hard Block) — Returned as `-32602` + `ruleId`. Agent must stop.
  • WARN (Soft Warning) — Returned as violation. Agent may continue with user confirmation.

Config Hot Update

Dynamic thresholds (similarity 0.7 / 0.9) are stored as `CognitionNode(type=HEURISTIC)`. Each update creates a new version node with the old node marked `supersededBy`. Requires `expertMode: true`.

Audit & Compliance

All injection decisions, config changes, and validation events are recorded via `MetricEvent` with async non-blocking writes. On database write failure, events fall back to `logs/fallback.log`.


MCP Resources

URI Type Content
`cognition://schema` application/json Cognition graph data model
`cognition://stats` application/json Node/edge counts + approvalRate7d
`cognition://docs` text/markdown Full tool documentation
`cognition://rules-changelog` application/json Versioned rule change log

MCP Tools

Tool Description readOnlyHint
`cognition_query` Query graph by context hash
`cognition_validate` Validate code against AST templates
`cognition_feedback` Provide feedback to refine traversal
`cognition_approve_injection` Approve/reject proposals with TTL
`cognition_update_config` Hot-update thresholds (expert mode)

Testing

```bash

Run all tests (118/118 passing)

npm test

Run specific suite

npx vitest run tests/protocol/ ```


Protocol Compliance

This server conforms to MCP Specification v1.29.0 and supports:

  • [x] initialize / initialized / ping / shutdown lifecycle
  • [x] tools/list + tools/call with JSON Schema input/output
  • [x] resources/list + resources/read with `cognition://` URI scheme
  • [x] StdioServerTransport and StreamableHTTPServerTransport
  • [x] Error codes: -32602 (invalid params), -32603 (internal), -32001 (timeout)
  • [x] Annotations: readOnlyHint, destructiveHint, openWorldHint

Contributing

We welcome contributions from the community! Here's how you can get involved:

  • Report a bug: Open an issue with reproduction steps.
  • Suggest a feature: Start a discussion to gather feedback before implementation.
  • Submit a PR: Follow the guidelines in CONTRIBUTING.md.

For major changes, please open an issue first to discuss what you would like to change.

🟢 New to the project?

Looking for a place to start? Check out our Good First Issues — they're specifically scoped for first-time contributors and include detailed context, acceptance criteria, and file references.


License

Copyright (c) 2026 熊高锐

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Full license text: LICENSE.

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