Major refactor to fix Bedrock + MCP compatibility issues:
- Removed Responses API approach (doesn't work with Bedrock)
- Added execute_mcp_tool() to manually call tools via /mcp/call_tool
- Rewrote get_available_mcp_tools() to return OpenAI function format
- Implemented manual tool execution loop with max 5 iterations
- Tool results are sent back to model in standard tool response format
- Removed query_needs_tools() function (no longer needed)
How it works:
1. Fetch MCP tools from /v1/mcp/tools and convert to OpenAI format
2. Call chat.completions.create() with tools array
3. When model requests tool calls, execute via POST /mcp/call_tool
4. Send results back to model with role="tool"
5. Loop until model provides final response
This bypasses the broken Responses API and uses working endpoints
that are compatible with AWS Bedrock + LiteLLM MCP integration.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Implements smart tool selection based on query content:
- Adds query_needs_tools() function to detect tool-requiring queries
- Sets tool_choice="required" for queries needing GitHub/time/weather/search
- Sets tool_choice="auto" for general conversation
- Adds debug logging for tool choice decisions
This fixes the issue where MCP tools were configured but not being used
because tool_choice defaulted to "auto" and the model opted not to use them.
Query detection keywords include:
- Time/date operations (time, clock, date, now, current)
- Weather queries (weather, temperature, forecast)
- GitHub operations (repo, code, file, commit, PR, issue)
- Search/lookup operations (search, find, get, fetch, retrieve)
- File operations (read, open, check, list, contents)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Key changes:
- Upgrade OpenAI SDK from 1.x to 2.x (required for responses API)
- Update get_ai_response to use developer role for system prompts
- Improve response extraction with output_text shorthand
- Add enhanced debug logging for troubleshooting
- Add traceback logging for better error diagnostics
This fixes the "'OpenAI' object has no attribute 'responses'" error
and enables proper MCP tool auto-execution through LiteLLM.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Major refactoring to properly integrate with LiteLLM's Responses API, which handles
MCP tool execution automatically instead of requiring manual tool call loops.
Key changes:
- Switched from chat.completions.create() to client.responses.create()
- Use "server_url": "litellm_proxy" to leverage LiteLLM as MCP gateway
- Set "require_approval": "never" for fully automatic tool execution
- Simplified get_available_mcp_tools() to get_available_mcp_servers()
- Removed manual OpenAI tool format conversion (LiteLLM handles this)
- Updated response extraction to use output[0].content[0].text format
- Convert system prompts to user role for Responses API compatibility
Technical improvements:
- LiteLLM now handles the complete tool calling loop automatically
- No more placeholder responses - actual MCP tools will execute
- Cleaner code with ~100 fewer lines
- Better separation between tools-enabled and tools-disabled paths
- Proper error handling for Responses API format
Responses API benefits:
- Single API call returns final response with tool results integrated
- Automatic tool discovery, execution, and result formatting
- No manual tracking of tool_call_ids or conversation state
- Native MCP support via server_label configuration
Documentation:
- Added comprehensive litellm-mcp-research.md with API examples
- Documented Responses API vs chat.completions differences
- Included Discord bot migration patterns
- Covered authentication, streaming, and tool restrictions
Next steps:
- Test with actual Discord interactions
- Verify GitHub MCP tools execute correctly
- Monitor response extraction for edge cases
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Major improvements to LiteLLM Discord bot with MCP (Model Context Protocol) tools support:
Features added:
- MCP tools discovery and integration with LiteLLM proxy
- Fetch and convert 40+ GitHub MCP tools to OpenAI format
- Tool calling flow with placeholder execution (pending MCP endpoint confirmation)
- Dynamic tool injection based on LiteLLM MCP server configuration
- Enhanced system prompt with tool usage guidance
- Added ENABLE_TOOLS environment variable for easy toggle
- Comprehensive debug logging for troubleshooting
Technical changes:
- Added httpx>=0.25.0 dependency for async MCP API calls
- Implemented get_available_mcp_tools() to query /v1/mcp/server and /v1/mcp/tools endpoints
- Convert MCP tool schemas to OpenAI function calling format
- Detect and handle tool_calls in model responses
- Added system_prompt.txt for customizable bot behavior
- Updated README with better documentation and setup instructions
- Created claude.md with detailed development notes and upgrade roadmap
Configuration:
- New ENABLE_TOOLS flag in .env to control MCP integration
- DEBUG_LOGGING for detailed execution logs
- System prompt file support for easy customization
Known limitations:
- Tool execution currently uses placeholders (MCP execution endpoint needs verification)
- Limited to 50 tools to avoid overwhelming the model
- Requires LiteLLM proxy with MCP server configured
Next steps:
- Verify correct LiteLLM MCP tool execution endpoint
- Implement actual tool execution via MCP proxy
- Test end-to-end GitHub operations through Discord
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
