gabiteodoru/qmcp
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qmcp is a Model Context Protocol (MCP) server designed for q/kdb+ integration, providing AI systems with controlled access to q/kdb+ databases for development and debugging workflows.
connect_to_q
Connect to q server with fallback logic
query_q
Execute q commands and return results
set_timeout_switch_to_async
Configure when queries switch to async mode
set_timeout_interrupt_q
Configure when to send SIGINT to cancel queries
set_timeout_connection
Configure connection timeout
get_timeout_settings
View current timeout configuration
get_current_task_status
Check status of running async query
get_current_task_result
Retrieve result of completed async query
qmcp Server
A Model Context Protocol (MCP) server for q/kdb+ integration.
MCP is an open protocol created by Anthropic that enables AI systems to interact with external tools and data sources. While currently supported by Claude (Desktop and CLI), the open standard allows other LLMs to adopt it in the future.
Features
- Connect to q/kdb+ servers
- Execute q queries and commands
- Persistent connection management
- Intelligent async query handling with configurable timeouts
- Programmatic query cancellation (Ctrl+C equivalent)
- Graceful handling of long-running queries
- NEW: Qython language translator (Experimental Alpha)
Windows Users: WSL Recommendation
ā ļø Important for Windows users: For optimal functionality, it is highly recommended to run both the MCP server and your q session inside WSL (Windows Subsystem for Linux). This ensures the server can interrupt infinite loops and runaway queries that LLMs might accidentally generate.
Running the MCP server on Windows (outside WSL) disables SIGINT-based query interruption functionality, which is critical for escaping problematic queries during AI-assisted development sessions.
Architecture & Design Philosophy
Intended Goals
qmcp is designed to provide AI coding assistants with controlled access to q/kdb+ databases for development and debugging workflows:
- Development-Focused: Optimized for coding tools working with debug/dev q servers
- Query Control: AI can interrupt long-running queries (equivalent to developer Ctrl+C)
- Predictable Behavior: Sequential execution prevents resource conflicts during development
- Configurable Timeouts: Customizable timing for different development scenarios
Design Logic
The server architecture makes deliberate choices for AI-assisted development workflows:
Single Connection Model
- Why: Simplifies development debugging - one connection, clear state
- Benefit: Matches typical developer workflow with single q session
- Implementation: One persistent connection per MCP session
Sequential Query Execution
- Why: Development environments don't need concurrent query support
- Benefit: Predictable resource usage, easier debugging, prevents query interference
- Implementation: New queries rejected while another is running
Smart Async Switching with Configurable Timeouts
Fast Query (< async switch timeout) ā Return result immediately
Slow Query (> async switch timeout) ā Switch to async mode
ā Auto-interrupt after interrupt timeout (if configured)
- Why: Keeps AI coding sessions responsive while allowing complex development queries
- Benefit: Immediate feedback for quick queries, progress tracking for analysis
- Customization: All timeouts configurable via MCP tools
AI-Controlled Query Interruption
- Why: AI coding tools need ability to cancel runaway queries (like developer Ctrl+C)
- How: MCP server locates q process by port and sends SIGINT after configurable timeout
- Benefit: Prevents development sessions from hanging on problematic queries
- Limitations: SIGINT functionality disabled when:
- MCP server runs on Windows (outside WSL)
- MCP server and q session run on opposite sides of WSL/Windows divide
Development-Oriented Process Management
- Why: Coding tools work with user-managed development q servers
- Benefit: Developer controls q server lifecycle, AI controls query execution
- Design: MCP server provides query interruption capability without server lifecycle management
Why This Design Makes Sense for Coding Tools
- Development Workflow: Matches how developers interact with q - single session, iterative queries
- AI Safety: Prevents AI from overwhelming development environments with concurrent requests
- Debugging-Friendly: Sequential execution makes it easier to trace issues
- Responsive: Async handling prevents AI coding sessions from blocking
- Configurable: Timeouts can be tuned for different development scenarios
This architecture provides AI coding assistants with effective q/kdb+ access while maintaining the predictable, controlled environment that development workflows require.
Requirements
- Python 3.8+
- Access to a q/kdb+ server
uv
(for lightweight installation) orpip
(for full installation)
Quick Start
For first-time users, the fastest way to get started:
- Start a q server:
q -p 5001
- Add qmcp to Claude CLI:
claude mcp add qmcp "uv run qmcp/server.py"
- Start using Claude CLI:
Then interact with qmcp:
claude
> connect to port 5001 and compute 2+2 ā qmcp:connect_to_q (MCP)(host: "5001") āæ true ā qmcp:query_q (MCP)(command: "2+2") āæ 4
Installation
Lightweight Installation (Claude CLI only)
Run directly with uv (no pip installation required, may be slower on startup; best for trying it out at first):
claude mcp add qmcp "uv run qmcp/server.py"
Full Installation
Option 1: pip (recommended for global use)
pip install qmcp
Note: Consider using a virtual environment to avoid dependency conflicts:
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
pip install qmcp
Option 2: uv (for project-specific use)
# One-time execution (downloads dependencies each time)
uv run qmcp
# Or for frequent use, sync dependencies first
uv sync
uv run qmcp
Adding to Claude CLI
After full installation, add the server to Claude CLI:
claude mcp add qmcp qmcp
Adding to Claude Desktop
Add to your Claude Desktop configuration file:
{
"mcpServers": {
"qmcp": {
"command": "qmcp"
}
}
}
For uv-based installation:
{
"mcpServers": {
"qmcp": {
"command": "uv",
"args": [
"--directory",
"/absolute/path/to/qmcp",
"run",
"qmcp"
]
}
}
}
Usage
Starting the MCP Server
After full installation:
qmcp
With lightweight installation: The server starts automatically when Claude CLI uses it (no manual start needed).
Environment Variables
Q_DEFAULT_HOST
- Default connection info in format:host
,host:port
, orhost:port:user:passwd
Connection Fallback Logic
The connect_to_q(host)
tool uses flexible fallback logic:
- Full connection string (has colons): Use directly, ignore
Q_DEFAULT_HOST
connect_to_q("myhost:5001:user:pass")
- Port number only: Combine with
Q_DEFAULT_HOST
or uselocalhost
connect_to_q(5001)
ā UsesQ_DEFAULT_HOST
settings with port 5001
- No parameters: Use
Q_DEFAULT_HOST
directlyconnect_to_q()
ā UsesQ_DEFAULT_HOST
as-is
- Hostname only: Use as hostname with
Q_DEFAULT_HOST
port/auth or default portconnect_to_q("myhost")
ā Combines withQ_DEFAULT_HOST
settings
Tool Stability Status
Production-Ready Tools:
connect_to_q
- Stable connection management with fallback logicquery_q
- Execute queries with intelligent async timeout controlset_timeout_switch_to_async
- Configure when queries switch to async modeset_timeout_interrupt_q
- Configure when to send SIGINT to cancel queriesset_timeout_connection
- Configure connection timeoutget_timeout_settings
- View current timeout configurationget_current_task_status
- Check status of running async queryget_current_task_result
- Retrieve result of completed async queryinterrupt_current_query
- Send SIGINT to interrupt running queries
Experimental Tools (Alpha):
translate_qython_to_q
- ā ļø EXPERIMENTAL: Python-like syntax to q translator- Qython supports:
do n times:
,converge()
,reduce()
,range()
- Limited vocabulary, may produce incorrect code
- Please verify all output before use
- Report bugs at GitHub Issues
- Qython supports:
Known Limitations
When using the MCP server, be aware of these limitations:
Query Interruption (SIGINT) Limitations
- Windows Platform: Query interruption disabled when MCP server runs on Windows (outside WSL)
- Cross-Platform Setup: Query interruption disabled when MCP server and q session run on opposite sides of WSL/Windows divide
- Impact: LLM cannot automatically escape infinite loops or cancel runaway queries in these configurations
Data Conversion Limitations
- Keyed tables: Operations like
1!table
may fail during pandas conversion - String vs Symbol distinction: q strings and symbols may appear identical in output
- Type ambiguity: Use q's
meta
andtype
commands to determine actual data types when precision matters - Pandas conversion: Some q-specific data structures may not convert properly to pandas DataFrames
For type checking, use:
meta table / Check table column types and structure
type variable / Check variable type
WSL2 Port Communication (Windows Users)
Skip this section if you're not on Windows.
Since Claude CLI is WSL-only on Windows, but you might want to use Windows IDEs or tools to connect to your q server, you need proper port communication between WSL2 and Windows.
WSL2 Configuration for Port Communication
.wslconfig File Setup
Location: C:\Users\{YourUsername}\.wslconfig
Add mirrored networking configuration:
# Mirrored networking mode for seamless port communication
networkingMode=mirrored
dnsTunneling=true
firewall=true
autoProxy=true
Restart WSL2
Run from Windows PowerShell/CMD (NOT from within WSL):
wsl --shutdown
# Wait a few seconds, then start WSL again
Verify Configuration
Check if mirrored networking is active:
ip addr show
cat /etc/resolv.conf
Test Port Communication
Test WSL2 ā Windows (localhost):
# In WSL2, start a server
python3 -m http.server 8000
# In Windows browser or PowerShell
curl http://localhost:8000
Test Windows ā WSL2 (localhost):
# In Windows PowerShell
python -m http.server 8001
# In WSL2
curl http://localhost:8001
What Mirrored Networking Provides
- ā Direct localhost communication both ways
- ā No manual port forwarding needed
- ā Better VPN compatibility
- ā Simplified networking (Windows and WSL2 share network interfaces)
- ā Firewall rules automatically handled
ā ļø Port 5000 Special Case
Issue: Port 5000 has limited mirrored networking support due to Windows service binding.
Root Cause:
- Windows
svchost
service binds to127.0.0.1:5000
(localhost only) - Localhost-only bindings are not fully mirrored between Windows and WSL2
- This creates an exception to the general mirrored networking functionality
Port 5000 Communication Matrix:
- ā Windows ā Windows: Works (same localhost)
- ā WSL2 ā Windows: Fails (different localhost interpretation)
- ā WSL2 ā WSL2: Works (same environment)
Solutions for Port 5000:
- Use different ports: 5001, 5002, etc. (recommended)
- Stop Windows service: If not needed
- Traditional port forwarding: For specific use cases
Common Services That May Have Localhost-Only Binding
- Flask development servers (default
127.0.0.1:5000
) - UPnP Device Host service
- Windows Media Player Network Sharing
- Various development tools
Known Limitations of Mirrored Networking
- Localhost-only services: Not fully mirrored (as confirmed with port 5000)
- mDNS doesn't work in mirrored mode
- Some Docker configurations may have issues
- Requires Windows 11 22H2+ (build 22621+)