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64 changes: 64 additions & 0 deletions .github/skills/mcp-protocol-debugging/SKILL.md
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---
name: mcp-protocol-debugging
description: Guide for exercising and debugging this repo's MCP JSON-RPC server (mcp_server/main.py), including capability negotiation (initialize/tools/list), tool calls, and error handling. Use when asked to verify, debug, or extend MCP support in self-correcting-executor.
---

This repo ships a canonical JSON-RPC MCP server at `mcp_server/main.py`
(`MCPServer` class), independent from the FastAPI-based
`mcp_server/real_mcp_server.py`. Use this process to verify or debug MCP
behavior:

1. **Confirm the baseline capability negotiation works** by driving the
server directly in Python (no transport needed for debugging):

```python
import asyncio
from mcp_server.main import MCPServer

async def main():
server = MCPServer()
# 1. initialize — must return serverInfo + capabilities.tools/resources
init = await server.handle_request({
"jsonrpc": "2.0", "id": 1, "method": "initialize",
"params": {"clientInfo": {"name": "debug-client", "version": "1.0"}},
})
print(init)

# 2. tools/list — must match the tools advertised in `initialize`
print(await server.handle_request(
{"jsonrpc": "2.0", "id": 2, "method": "tools/list", "params": {}}
))

# 3. tools/call — must execute real logic (code_analyzer, protocol_validator,
# self_corrector), never mocked/simulated results
print(await server.handle_request({
"jsonrpc": "2.0", "id": 3, "method": "tools/call",
"params": {"name": "code_analyzer", "arguments": {"code": "x = 1"}},
}))

asyncio.run(main())
```

2. **Run the automated baseline test** that pins this behavior down:

```bash
python -m pytest tests/test_mcp_baseline.py -v
```

3. **When adding a new MCP tool or resource**, update all three of:
- `MCPServer._setup_tools` / `_setup_resources` (declares the capability)
- the corresponding `_execute_<tool_name>` method (real implementation,
never a stub/mock — this repo enforces "no mocks in production", see
`tests/test_mcp_compliance.py::test_no_placeholder_code_in_production`)
- `tests/test_mcp_baseline.py` and/or `tests/test_mcp_compliance.py` to
cover the new capability.

4. **Unknown or malformed methods must degrade gracefully**: `handle_request`
should always return a well-formed JSON-RPC response with an
`{"error": {"code": ..., "message": ...}}` field rather than raising
an unhandled exception — verify this whenever you touch `_get_handler`.

5. For the FastAPI-based server (`mcp_server/real_mcp_server.py`) or the
quantum-specific server (`quantum_mcp_server/quantum_mcp.py`), apply the
same principle: prove `initialize`/capability discovery works live before
relying on more advanced features (subscriptions, resource reads, etc.).
53 changes: 53 additions & 0 deletions .github/skills/quantum-connector-testing/SKILL.md
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---
name: quantum-connector-testing
description: Guide for testing connectors/dwave_quantum_connector.py and other quantum MCP tools in self-correcting-executor without requiring a live D-Wave QPU token, while respecting this repo's "no simulation/mocks in production" convention. Use when asked to test, debug, or extend quantum computing integration.
---

This repo's D-Wave integration (`connectors/dwave_quantum_connector.py`,
`mcp_server/quantum_tools.py`, `quantum_mcp_server/quantum_mcp.py`) is
intentionally built against the **real** D-Wave Ocean SDK and Leap cloud
service — it must never silently fall back to a local simulator/annealer in
production code paths (see the removed `SimulatedAnnealingSampler` import
and `tests/test_mcp_compliance.py::test_quantum_requires_real_qpu`).

When testing or extending this code:

1. **Check for `DWAVE_AVAILABLE` / `DWAVE_API_TOKEN` before assuming a QPU is
reachable.** Tests and scripts should `pytest.skip(...)` (not fabricate
results) when the token isn't set, mirroring the existing pattern in
`tests/test_mcp_compliance.py::test_quantum_requires_real_qpu`:

```python
import os
import pytest

if not os.getenv("DWAVE_API_TOKEN"):
pytest.skip("DWAVE_API_TOKEN not set - skipping quantum test")
```

2. **Test the non-quantum-hardware parts directly and deterministically:**
- Input validation / `QuantumResult` dataclass construction
- Problem formulation (`BinaryQuadraticModel` / `ConstrainedQuadraticModel`
building) using `dimod`, which runs locally without QPU access
- Error handling paths that should raise/propagate a `RuntimeError`
(e.g. `"No D-Wave QPU available"`) instead of silently simulating

3. **Never add a mock/simulated sampler as a fallback** in
`connectors/dwave_quantum_connector.py` or related production files —
this is explicitly checked by
`tests/test_mcp_compliance.py::test_no_placeholder_code_in_production`
and `test_data_processor_no_simulation`, which scan for
`mock`/`simulated`/`placeholder` strings in production directories
(`agents`, `connectors`, `mcp_server`, `protocols`).
Comment on lines +37 to +41

4. **Run the relevant test files** after any change:

```bash
python -m pytest tests/test_mcp_compliance.py -k quantum -v
python -m pytest test_real_dwave_quantum.py -v # requires DWAVE_API_TOKEN
```

5. If you need to demonstrate quantum problem formulation without hardware
access, use `simple_quantum_example.py` as a reference for building a
`BinaryQuadraticModel` locally, then document clearly that solving it on
real hardware requires a valid `DWAVE_API_TOKEN`.
142 changes: 142 additions & 0 deletions docs/REPO_MAP.md
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# Repo Map, Architecture & Agentic Workflow Checklist

This document maps `self-correcting-executor` for AI coding agents (Copilot
cloud agent, Copilot CLI, etc.) so an agent run can quickly orient itself
before making changes: what the repo does, how its pieces relate, what
already exists for MCP/agents/tools, and what to check before commit/merge.

## Repo tree (top level)

```
self-correcting-executor/
├── agents/ # A2A agent framework + MCP-enabled agents
├── analyzers/ # Static analysis helpers (pattern_detector, ...)
├── auth/ # Basic auth helpers
├── config/ # MCPConfig, component type definitions
├── connectors/ # MCP base + concrete connectors (D-Wave, GitHub, LLM, xAI)
├── docs/ # Architecture, planning & task docs (this file lives here)
├── fabric/ # Integrated MCP "fabric" / state continuity core
├── frontend/ # Vite/React UI
├── llm/ # Continuous learning system
├── mcp_runtime_template_hg/ # SDK/API/CLI template for MCP runtimes
├── mcp_server/ # Canonical JSON-RPC MCP server (main.py) + quantum tools
├── middleware/ # Security middleware
├── orchestrator.py, orchestrator_mapreduce.py # Task orchestration entrypoints
├── protocols/ # Pluggable "protocol" tasks executed by the orchestrator
├── quantum_mcp_server/ # Quantum-specific MCP server variant
├── scripts/ # Compliance/setup/cleanup scripts
├── tests/ + test_*.py # Pytest suites (see pytest.ini: testpaths = tests)
├── ui/ # Additional UI assets/guide
└── utils/ # Shared logger/tracker/registry utilities
```

## Mermaid diagram: high-level architecture

```mermaid
flowchart TD
subgraph Host["Host: AI Agent / Copilot"]
A[Agent orchestrator.py / orchestrator_mapreduce.py]
end

subgraph MCPServers["MCP Servers (this repo)"]
M1[mcp_server/main.py<br/>JSON-RPC MCP server]
M2[mcp_server/real_mcp_server.py]
M3[quantum_mcp_server/quantum_mcp.py]
end

subgraph Tools["Tools exposed via MCP"]
T1[code_analyzer]
T2[protocol_validator]
T3[self_corrector]
end

subgraph Connectors["Connectors"]
C1[dwave_quantum_connector.py]
C2[github_mcp_connector.py]
C3[llm_connector.py]
C4[xai_connector.py]
end

subgraph Protocols["protocols/*.py tasks"]
P1[data_processor]
P2[system_monitor]
P3[file_validator]
P4[...]
end

A -- "JSON-RPC: initialize / tools/list / tools/call" --> M1
M1 --> T1
M1 --> T2
M1 --> T3
A --> M2
A --> M3
M2 --> C1
M2 --> C2
M2 --> C3
M2 --> C4
Comment on lines +73 to +76
A --> Protocols
Protocols --> P1
Protocols --> P2
Protocols --> P3
Protocols --> P4
```

## Checklist for an agent run in this repo

Use this before proving/implementing anything live in this repo:

- [x] **Agents** — `agents/a2a_framework.py`, `agents/a2a_mcp_integration.py`
implement agent-to-agent (A2A) communication over MCP.
- [x] **Tools** — MCP tools are declared in `mcp_server/main.py`
(`code_analyzer`, `protocol_validator`, `self_corrector`).
- [x] **MCP** — Baseline JSON-RPC server exists (`mcp_server/main.py`) and is
verified live in `tests/test_mcp_baseline.py` (`initialize`,
`tools/list`, `tools/call`, and error handling for unknown methods).
- [ ] **Pull / Push / Commit / Merge** — Use `engine-tools-report_progress`
(or normal `git`/PR flow for humans); never push directly from an
agent sandbox. See `CONTRIBUTING.md`.
Comment on lines +95 to +97
- [ ] **Issues** — Track work items and link PRs with `Closes #<issue>`.
- [ ] **Code** — Run `python -m pytest tests/` (see `pytest.ini`) and the
lint config in `.flake8` before committing.
- [ ] **Deps** — `requirements.txt` (runtime), `requirements-ci.txt` /
`requirements-test.txt` (CI/tests), `frontend/package.json` (UI).
Dependabot is configured in `.github/dependabot.yml`.
- [ ] **Database** — `protocols/database_health_check.py`,
`utils/db_tracker.py` for DB-backed protocol tasks.
- [ ] **Actions** — `.github/workflows/python-ci.yml` and
`.github/workflows/frontend-ci.yml` run CI on push/PR.
- [ ] **Role assignment** — `middleware/security_middleware.py`,
`auth/basic_auth.py` for auth/authorization concerns.

## MCP capability negotiation baseline

Per the [MCP specification](https://modelcontextprotocol.io/specification/2026-07-28),
a host/server pair must be able to negotiate capabilities before any other
request. This repo's `mcp_server/main.py` implements the minimum required
surface:

| Method | Purpose |
| --- | --- |
| `initialize` | Returns `serverInfo` + `capabilities.tools` + `capabilities.resources` |
| `tools/list` | Lists available tools independently of `initialize` |
| `tools/call` | Executes a tool and returns real (non-mocked) results |
| `resources/list` / `resources/read` | Lists/reads MCP resources |
| `notifications/list` / `notifications/subscribe` | Baseline notification support |

This baseline is exercised live and asserted in
`tests/test_mcp_baseline.py`. Run it with:
Comment on lines +123 to +127

```bash
python -m pytest tests/test_mcp_baseline.py -v
```

## Related repo-specific skills

Two agent skills tailored to this repo live under `.github/skills/`:

- `mcp-protocol-debugging` — how to exercise and debug the `mcp_server/main.py`
JSON-RPC server directly (capability negotiation, tool calls, error cases).
- `quantum-connector-testing` — how to safely test `dwave_quantum_connector.py`
without requiring a live D-Wave QPU token, consistent with this repo's
"no mocks in production, real APIs only" convention (see
`tests/test_mcp_compliance.py`).
88 changes: 88 additions & 0 deletions tests/test_mcp_baseline.py
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#!/usr/bin/env python3
"""Baseline MCP capability negotiation tests.

These tests prove that the repository's JSON-RPC based MCP server
(`mcp_server/main.py`) implements the minimum handshake required for a host
to negotiate capabilities with the server: `initialize`, `tools/list`, and
`tools/call`. This is the smallest possible verification that MCP is
functional for this repo, per the Model Context Protocol specification
(https://modelcontextprotocol.io/specification).
"""

import pytest

from mcp_server.main import MCPServer, MCP_VERSION


@pytest.fixture
def mcp_server() -> MCPServer:
"""Create a fresh MCP server instance for each test."""
return MCPServer()


@pytest.mark.asyncio
async def test_initialize_declares_capabilities(mcp_server: MCPServer):
"""The 'initialize' handshake must advertise server info and capabilities."""
response = await mcp_server.handle_request(
{
"jsonrpc": "2.0",
"id": 1,
"method": "initialize",
"params": {"clientInfo": {"name": "test-client", "version": "1.0"}},
}
)

assert response["jsonrpc"] == "2.0"
assert response["id"] == 1
assert "error" not in response

result = response["result"]
assert result["serverInfo"]["mcpVersion"] == MCP_VERSION
assert "tools" in result["capabilities"]
assert "resources" in result["capabilities"]
tool_names = {tool["name"] for tool in result["capabilities"]["tools"]}
assert {"code_analyzer", "protocol_validator", "self_corrector"} <= tool_names


@pytest.mark.asyncio
async def test_tools_list_matches_advertised_capabilities(mcp_server: MCPServer):
"""'tools/list' must be callable independently of 'initialize'."""
response = await mcp_server.handle_request(
{"jsonrpc": "2.0", "id": 2, "method": "tools/list", "params": {}}
)

assert "error" not in response
tool_names = {tool["name"] for tool in response["result"]["tools"]}
assert {"code_analyzer", "protocol_validator", "self_corrector"} <= tool_names


@pytest.mark.asyncio
async def test_tools_call_executes_a_real_tool(mcp_server: MCPServer):
"""'tools/call' must invoke real tool logic, proving negotiation works end-to-end."""
response = await mcp_server.handle_request(
{
"jsonrpc": "2.0",
"id": 3,
"method": "tools/call",
"params": {
"name": "code_analyzer",
"arguments": {"code": "def f():\n return 1\n"},
},
}
)

assert "error" not in response
assert response["result"]["tool"] == "code_analyzer"


@pytest.mark.asyncio
async def test_unknown_method_returns_json_rpc_error(mcp_server: MCPServer):
"""Unsupported methods must return a well-formed JSON-RPC error, not crash."""
response = await mcp_server.handle_request(
{"jsonrpc": "2.0", "id": 4, "method": "not/a/real/method", "params": {}}
)

assert response["jsonrpc"] == "2.0"
assert response["id"] == 4
assert "error" in response
assert response["error"]["code"] == -32000
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