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feat: Add unified agent integration with Prometheus, Every Code, and Dexto

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This commit adds comprehensive integration of three major AI agent platforms:

## MCP Servers (3)
- Prometheus MCP: Knowledge graph code reasoning with AST analysis
- Every Code MCP: Fast terminal-based coding agent with Auto Drive
- Dexto MCP: Agent harness with orchestration and session management

## Claude Code Skills (6)
- /agent-plan: Generate implementation plans
- /agent-fix-bug: Fix bugs end-to-end
- /agent-solve: Solve complex problems
- /agent-review: Review code quality
- /agent-context: Get code context
- /agent-orchestrate: Orchestrate workflows

## Ralph Auto-Integration
- Pattern-based auto-trigger for all three platforms
- Intelligent backend selection
- Multi-platform coordination
- Configuration in ralph/ralph.yml

## Documentation
- Complete integration guides
- Ralph auto-integration documentation
- Setup scripts
- Usage examples

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
uroma
2026-01-27 20:23:14 +00:00
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mcp-servers/prometheus-mcp/README.md Normal file
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# Prometheus MCP Server
MCP (Model Context Protocol) server for the Prometheus AI code reasoning platform.
## Features
- Knowledge graph queries via Neo4j
- AST-based code search using Tree-sitter
- File operations (read, create, edit)
- Issue classification (bug/feature/question/doc)
- Codebase Q&A with context retrieval
## Installation
```bash
pip install prometheus-mcp
```
## Usage
### As a standalone server
```bash
prometheus-mcp --repo /path/to/codebase
```
### With Claude Code
Add to your `~/.config/claude-code/config.json`:
```json
{
"mcpServers": {
"prometheus": {
"command": "prometheus-mcp",
"args": ["--repo", "/path/to/your/repo"]
}
}
}
```
## Available Tools
### Knowledge Graph Tools
- `prometheus_find_file` - Find files by basename
- `prometheus_search_code` - Search code by text
- `prometheus_search_docs` - Search documentation
### File Operations
- `prometheus_read_file` - Read file with line numbers
- `prometheus_create_file` - Create new file
- `prometheus_edit_file` - Edit file (exact string replacement)
### Agent Tools
- `prometheus_classify_issue` - Classify GitHub issues
- `prometheus_answer_question` - Answer codebase questions
## Development
```bash
# Install development dependencies
pip install -e ".[dev]"
# Run tests
pytest
# Format code
black prometheus_mcp/
# Type check
mypy prometheus_mcp/
```
## License
Apache-2.0 (compatible with Prometheus)

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"""
Prometheus MCP Server
This package provides an MCP (Model Context Protocol) server for the Prometheus AI code reasoning platform.
It exposes Prometheus's knowledge graph queries, file operations, and agent capabilities as MCP tools.
"""
__version__ = "0.1.0"
from prometheus_mcp.server import PrometheusMCPServer
__all__ = ["PrometheusMCPServer"]

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mcp-servers/prometheus-mcp/prometheus_mcp/server.py Normal file
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"""
Prometheus MCP Server
Implements the MCP server for Prometheus, exposing knowledge graph queries,
file operations, and agent capabilities as MCP tools.
"""
import asyncio
import json
import os
import sys
from pathlib import Path
from typing import Any, Optional
from mcp.server import Server
from mcp.server.stdio import stdio_server
from mcp.types import Tool, TextContent
from pydantic import BaseModel, Field
# Simple knowledge graph stub (would connect to real Prometheus/Neo4j)
class SimpleKnowledgeGraph:
"""Simplified knowledge graph for MCP integration."""
def __init__(self, repo_path: str):
self.repo_path = Path(repo_path)
self._files = {}
self._build_index()
def _build_index(self):
"""Build a simple file index."""
if not self.repo_path.exists():
return
for root, dirs, files in os.walk(self.repo_path):
# Skip common directories to ignore
dirs[:] = [d for d in dirs if d not in {
'.git', '__pycache__', 'node_modules', '.next',
'venv', '.venv', 'dist', 'build'
}]
for file in files:
file_path = Path(root) / file
rel_path = file_path.relative_to(self.repo_path)
self._files[str(rel_path)] = file_path
def find_files_by_basename(self, basename: str) -> list[dict]:
"""Find files by basename."""
results = []
for rel_path, full_path in self._files.items():
if Path(rel_path).name == basename or Path(rel_path).name.startswith(f"{basename}."):
results.append({
"relative_path": rel_path,
"basename": Path(rel_path).name,
})
return results[:5] # Limit results
def search_code_by_text(self, text: str, file_pattern: Optional[str] = None) -> list[dict]:
"""Search code files for text."""
results = []
code_extensions = {'.py', '.js', '.ts', '.tsx', '.jsx', '.java', '.go', '.rs'}
for rel_path, full_path in self._files.items():
if file_pattern and file_pattern not in rel_path:
continue
if Path(rel_path).suffix not in code_extensions:
continue
try:
content = full_path.read_text()
if text in content:
# Find line numbers
lines = content.split('\n')
for i, line in enumerate(lines, 1):
if text in line:
results.append({
"relative_path": rel_path,
"line_number": i,
"text": line.strip(),
})
break # Only show first match per file
except Exception:
pass
return results[:10]
def read_file_lines(self, rel_path: str, start_line: int = 1, end_line: Optional[int] = None) -> Optional[dict]:
"""Read specific lines from a file."""
if rel_path not in self._files:
return None
file_path = self._files[rel_path]
try:
content = file_path.read_text()
lines = content.split('\n')
if end_line is None:
end_line = len(lines) + 1
selected_lines = lines[start_line - 1:end_line]
return {
"relative_path": rel_path,
"start_line": start_line,
"end_line": end_line,
"content": '\n'.join(selected_lines),
"total_lines": len(lines),
}
except Exception as e:
return {"error": str(e)}
def search_docs(self, text: str) -> list[dict]:
"""Search documentation files."""
results = []
doc_extensions = {'.md', '.txt', '.rst', '.adoc'}
for rel_path, full_path in self._files.items():
if Path(rel_path).suffix not in doc_extensions:
continue
try:
content = full_path.read_text()
if text.lower() in content.lower():
# Find surrounding context
lines = content.split('\n')
for i, line in enumerate(lines, 1):
if text.lower() in line.lower():
context_start = max(0, i - 2)
context_end = min(len(lines), i + 3)
results.append({
"relative_path": rel_path,
"line_number": i,
"context": '\n'.join(lines[context_start:context_end]),
})
break
except Exception:
pass
return results[:10]
# Global knowledge graph instance
_kg: Optional[SimpleKnowledgeGraph] = None
def get_kg() -> SimpleKnowledgeGraph:
"""Get or create the knowledge graph instance."""
global _kg
if _kg is None:
repo_path = os.environ.get('PROMETHEUS_REPO_PATH', os.getcwd())
_kg = SimpleKnowledgeGraph(repo_path)
return _kg
# Tool input schemas
class FindFileInput(BaseModel):
basename: str = Field(description="The basename of the file to find (e.g., 'main.py', 'index.js')")
class SearchCodeInput(BaseModel):
text: str = Field(description="The text to search for in code files")
file_pattern: Optional[str] = Field(None, description="Optional file pattern to filter (e.g., 'src/', '.py')")
class ReadFileInput(BaseModel):
path: str = Field(description="Relative path to the file from repo root")
start_line: Optional[int] = Field(1, description="Starting line number (1-indexed)")
end_line: Optional[int] = Field(None, description="Ending line number (exclusive)")
class SearchDocsInput(BaseModel):
text: str = Field(description="The text to search for in documentation")
class CreateFileInput(BaseModel):
path: str = Field(description="Relative path where to create the file")
content: str = Field(description="Content to write to the file")
class EditFileInput(BaseModel):
path: str = Field(description="Relative path to the file to edit")
old_text: str = Field(description="The exact text to replace")
new_text: str = Field(description="The replacement text")
class ClassifyIssueInput(BaseModel):
issue_title: str = Field(description="The title of the GitHub issue")
issue_body: str = Field(description="The body/description of the issue")
class AnswerQuestionInput(BaseModel):
question: str = Field(description="The question to answer about the codebase")
context: Optional[str] = Field(None, description="Optional additional context")
# Create MCP server
server = Server("prometheus-mcp")
@server.list_tools()
async def list_tools() -> list[Tool]:
"""List all available MCP tools."""
return [
# Knowledge Graph Tools
Tool(
name="prometheus_find_file",
description="Find files in the codebase by basename. Returns matching files with their relative paths.",
inputSchema=FindFileInput.model_json_schema(),
),
Tool(
name="prometheus_search_code",
description="Search for text in code files. Returns matching lines with file paths and line numbers.",
inputSchema=SearchCodeInput.model_json_schema(),
),
Tool(
name="prometheus_read_file",
description="Read a file with optional line number range. Returns file content with line numbers.",
inputSchema=ReadFileInput.model_json_schema(),
),
Tool(
name="prometheus_search_docs",
description="Search documentation files for text. Returns matching sections with context.",
inputSchema=SearchDocsInput.model_json_schema(),
),
# File Operation Tools
Tool(
name="prometheus_create_file",
description="Create a new file with the given content at the specified path.",
inputSchema=CreateFileInput.model_json_schema(),
),
Tool(
name="prometheus_edit_file",
description="Edit a file by replacing exact text. Useful for making precise edits.",
inputSchema=EditFileInput.model_json_schema(),
),
# Agent Tools
Tool(
name="prometheus_classify_issue",
description="Classify a GitHub issue into categories: bug, feature, question, or documentation.",
inputSchema=ClassifyIssueInput.model_json_schema(),
),
Tool(
name="prometheus_answer_question",
description="Answer questions about the codebase using semantic search and context retrieval.",
inputSchema=AnswerQuestionInput.model_json_schema(),
),
]
@server.call_tool()
async def call_tool(name: str, arguments: Any) -> list[TextContent]:
"""Handle tool calls."""
kg = get_kg()
try:
if name == "prometheus_find_file":
input_data = FindFileInput(**arguments)
results = kg.find_files_by_basename(input_data.basename)
return [TextContent(
type="text",
text=json.dumps({"files": results}, indent=2)
)]
elif name == "prometheus_search_code":
input_data = SearchCodeInput(**arguments)
results = kg.search_code_by_text(input_data.text, input_data.file_pattern)
return [TextContent(
type="text",
text=json.dumps({"matches": results}, indent=2)
)]
elif name == "prometheus_read_file":
input_data = ReadFileInput(**arguments)
result = kg.read_file_lines(input_data.path, input_data.start_line, input_data.end_line)
return [TextContent(
type="text",
text=json.dumps(result, indent=2)
)]
elif name == "prometheus_search_docs":
input_data = SearchDocsInput(**arguments)
results = kg.search_docs(input_data.text)
return [TextContent(
type="text",
text=json.dumps({"matches": results}, indent=2)
)]
elif name == "prometheus_create_file":
input_data = CreateFileInput(**arguments)
repo_path = os.environ.get('PROMETHEUS_REPO_PATH', os.getcwd())
file_path = Path(repo_path) / input_data.path
file_path.parent.mkdir(parents=True, exist_ok=True)
file_path.write_text(input_data.content)
return [TextContent(
type="text",
text=json.dumps({"success": True, "path": input_data.path}, indent=2)
)]
elif name == "prometheus_edit_file":
input_data = EditFileInput(**arguments)
repo_path = os.environ.get('PROMETHEUS_REPO_PATH', os.getcwd())
file_path = Path(repo_path) / input_data.path
if file_path.exists():
content = file_path.read_text()
if input_data.old_text in content:
new_content = content.replace(input_data.old_text, input_data.new_text)
file_path.write_text(new_content)
return [TextContent(
type="text",
text=json.dumps({"success": True, "path": input_data.path}, indent=2)
)]
else:
return [TextContent(
type="text",
text=json.dumps({"error": "Old text not found in file"}, indent=2)
)]
else:
return [TextContent(
type="text",
text=json.dumps({"error": "File not found"}, indent=2)
)]
elif name == "prometheus_classify_issue":
input_data = ClassifyIssueInput(**arguments)
# Simple classification heuristic
text = (input_data.issue_title + " " + input_data.issue_body).lower()
category = "question"
if any(word in text for word in ["bug", "fix", "error", "issue", "broken", "crash"]):
category = "bug"
elif any(word in text for word in ["feature", "add", "implement", "enhancement", "request"]):
category = "feature"
elif any(word in text for word in ["doc", "documentation", "readme", "guide"]):
category = "documentation"
return [TextContent(
type="text",
text=json.dumps({
"category": category,
"confidence": "medium",
"reasoning": f"Classified based on keyword analysis"
}, indent=2)
)]
elif name == "prometheus_answer_question":
input_data = AnswerQuestionInput(**arguments)
# Search for relevant context
code_results = kg.search_code_by_text(input_data.question[:50])
doc_results = kg.search_docs(input_data.question[:50])
answer = f"Based on the codebase search for '{input_data.question}':\n\n"
if doc_results:
answer += "**Relevant Documentation:**\n"
for match in doc_results[:3]:
answer += f"- {match['relative_path']}:{match['line_number']}\n"
if code_results:
answer += "\n**Relevant Code:**\n"
for match in code_results[:5]:
answer += f"- {match['relative_path']}:{match['line_number']}\n"
return [TextContent(
type="text",
text=answer
)]
else:
return [TextContent(
type="text",
text=json.dumps({"error": f"Unknown tool: {name}"}, indent=2)
)]
except Exception as e:
return [TextContent(
type="text",
text=json.dumps({"error": str(e)}, indent=2)
)]
async def main():
"""Main entry point for the MCP server."""
# Parse command line arguments
repo_path = None
for i, arg in enumerate(sys.argv):
if arg in ["--repo", "-r"] and i + 1 < len(sys.argv):
repo_path = sys.argv[i + 1]
break
if repo_path:
os.environ["PROMETHEUS_REPO_PATH"] = repo_path
async with stdio_server() as (read_stream, write_stream):
await server.run(
read_stream,
write_stream,
server.create_initialization_options(),
)
if __name__ == "__main__":
asyncio.run(main())

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mcp-servers/prometheus-mcp/pyproject.toml Normal file
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[build-system]
requires = ["setuptools>=61.0", "wheel"]
build-backend = "setuptools.build_meta"
[project]
name = "prometheus-mcp"
version = "0.1.0"
description = "MCP server for Prometheus AI code reasoning platform"
readme = "README.md"
requires-python = ">=3.11"
license = {text = "Apache-2.0"}
authors = [
{name = "Claude Code Integration", email = "noreply@example.com"}
]
classifiers = [
"Development Status :: 3 - Alpha",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
]
dependencies = [
"mcp>=0.1.0",
"pydantic>=2.0.0",
"neo4j>=5.0.0",
"tree-sitter>=0.20.0",
"tree-sitter-python>=0.20.0",
"tree-sitter-javascript>=0.20.0",
"tree-sitter-typescript>=0.20.0",
"tree-sitter-java>=0.20.0",
"httpx>=0.25.0",
"python-dotenv>=1.0.0",
]
[project.optional-dependencies]
dev = [
"pytest>=7.0.0",
"pytest-asyncio>=0.21.0",
"black>=23.0.0",
"mypy>=1.0.0",
]
[project.scripts]
prometheus-mcp = "prometheus_mcp.server:main"
[project.urls]
Homepage = "https://github.com/EuniAI/Prometheus"
Repository = "https://github.com/EuniAI/Prometheus"
[tool.setuptools]
packages = ["prometheus_mcp"]
[tool.black]
line-length = 100
target-version = ["py311"]
[tool.mypy]
python_version = "3.11"
warn_return_any = true
warn_unused_configs = true