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QWED-AI

QWED-MCP

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MCP Server for QWED Verification — Bring deterministic verification to Claude Desktop, VS Code, and any MCP-compatible AI assistant.

📚 Full Documentation: docs.qwedai.com/mcp

⚡ Quick Install

pip install qwed-mcp

Related MCP server: SymPy Sandbox MCP

🚀 Setup with Claude Desktop

Step 1: Find your config file

OS

Path

Windows

%APPDATA%\Claude\claude_desktop_config.json

macOS

~/Library/Application Support/Claude/claude_desktop_config.json

Linux

~/.config/Claude/claude_desktop_config.json

Step 2: Add QWED-MCP

macOS/Linux:

{
  "mcpServers": {
    "qwed-verification": {
      "command": "qwed-mcp"
    }
  }
}

Windows (use python -m):

{
  "mcpServers": {
    "qwed-verification": {
      "command": "python",
      "args": ["-m", "qwed_mcp.server"]
    }
  }
}

Step 3: Restart Claude Desktop

Quit completely (system tray → Quit) and reopen.

Step 4: Test it!

Ask Claude:

"Write a python script that verifies a 10,000 investment at 7.5% for 5 years using the qwed_new math engine, and run it using execute_python_code."

⚠️ Migration Note: Deprecation of verify_* Tools

To solve "context bloat" and align with the new MCP standard (RFC-9728), all 1:1 functional tools (e.g., verify_math, verify_sql, verify_code) have been removed as of v0.2.1.

They have been replaced with a single, highly capable tool: 👉 execute_python_code

Before:

"Use verify_math to check this formula." (Claude loads 14 different tool schemas into context)

After:

"Use execute_python_code to write and run a script that imports qwed_new.engines.math_engine to verify..." (Claude loads 1 tool schema into context)

If you see an "Unknown tool" error, it means Claude is trying to use a legacy tool. Simply tell Claude: "The verify_* tools are removed. Use execute_python_code to natively write and run a Python verification script."

🔧 Available Tools

Tool

Description

Use Case

execute_python_code

Subprocess Execution

The single entrypoint for all QWED capabilities. Executes dynamically generated Python code in a subprocess with restricted environment variables. Note: Runs with server privileges; ensure inputs are trusted.

💡 Example Prompts for Claude

Note: Claude already knows how to use QWED natively via standard Python imports.

Financial Calculations

A bank says: "Invest $10,000 at 7.5% compounded quarterly for 5 years = $14,356.29"
Please write a short Python script using the standard compound interest formula to verify this, and run it with execute_python_code.

Loan EMI Verification

Verify: ₹10,00,000 loan at 9% for 5 years = EMI of ₹20,758
Write a python script importing necessary tools to verify this EMI calculation, and execute it using execute_python_code.

Complex Reasoning Workflows (The Power of Python)

Read the user terms in the attached document. 
1. Use execute_python_code to extract and verify the legal clauses using qwed_legal.
2. In the same script, verify if the referenced financial penalties align with the allowed boundaries.

🏗️ How It Works

┌───────────────────────────────────────────┐
│      Claude Desktop / VS Code             │
│           (MCP Client)                    │
└─────────────────┬─────────────────────────┘
                  │ MCP Protocol (JSON-RPC)
                  ▼
┌───────────────────────────────────────────┐
│           QWED-MCP Server                 │
├───────────────────────────────────────────┤
│ execute_python_code()                     │
│  └─► Subprocess Execution (Restricted Env)│
│       └─► Native QWED library execution   │
└───────────────────────────────────────────┘

🎯 Why QWED-MCP?

Note: Subprocess execution provides answers/checks purely based on what QWED SDK methods are invoked inside the executed scripts. Execution itself does not guarantee injection detection without specific SDK calls.

Without QWED-MCP

With QWED-MCP

LLM calculates → 95% correct

Executes Python script calling qwed_finance → 100% correct

LLM writes SQL → might inject

Script uses qwed_new analyzer → injection detected

LLM reasons → might be wrong

Z3 solver executed via SDK → formally proven

LLM codes → might be unsafe

AST check script executed → security checked

💡 What QWED-MCP Is (and Isn't)

✅ QWED-MCP IS:

  • MCP Server that adds verification tools to Claude Desktop and VS Code

  • Deterministic — uses SymPy (math), Z3 (logic), AST (code) for exact verification

  • Open source — works with any MCP-compatible AI assistant

  • A safety layer — catches LLM hallucinations in real-time

❌ QWED-MCP is NOT:

  • A replacement for Claude — it enhances Claude with verification tools

  • A chatbot — it's a backend server that Claude calls

  • Internet-connected — all verification happens locally

  • A fine-tuned model — uses symbolic engines, not ML

Think of QWED-MCP as giving Claude a "calculator" for math and a "theorem prover" for logic.

Claude reasons. QWED-MCP verifies.

🆚 How We're Different from Other MCP Servers

Aspect

Other MCP Servers

QWED-MCP

Purpose

Connect to APIs, databases, files

Verify LLM outputs

Approach

Fetch external data

Compute deterministic proofs

Engines

API wrappers

SymPy, Z3, AST analyzers

Accuracy

Depends on data source

100% mathematically proven

Offline

Often need internet

Fully local, no APIs

With Claude Desktop

┌───────────────────┐     ┌───────────────────────┐     ┌───────────────────┐
│      Claude       │     │       QWED-MCP        │     │  Verified Answer  │
│ "What's d/dx x³?" │ ──► │ execute_python_code() │ ──► │      "3x²" ✓      │
│ "Write script to  │     │ Runs SymPy natively   │     │ (STDOUT Captured) │
│ check."           │     └───────────────────────┘     └───────────────────┘
└───────────────────┘

🔒 Security & Privacy

All verification happens locally. Nothing is sent to external servers.

Concern

QWED-MCP Approach

Data Transmission

❌ No external API calls

Storage

❌ Nothing logged or stored

Dependencies

✅ Local engines (SymPy, Z3)

Code Analysis

✅ Your code never leaves your machine

Perfect for:

  • Enterprises with strict security policies

  • Air-gapped development environments

  • Sensitive code review workflows

❓ FAQ

Yes! Open source under Apache 2.0. Use it commercially, modify it, distribute it.

QWED-MCP works with any MCP-compatible client. VS Code with Claude extension supports MCP, so yes!

No. QWED-MCP runs entirely locally. No API keys, no cloud calls.

QWED-Core is the Python library. QWED-MCP wraps it as an MCP server so Claude can use it as a tool.

Yes! The server is extensible. Fork it and add your custom @mcp.tool() functions.

🗺️ Roadmap

✅ Released (v0.2.2)

  • Context bloat resolution (RFC-9728 compatibility)

  • Unified execute_python_code environment

  • Secure process isolation (env-restricted) and robust timeouts

  • Claude Desktop integration

  • Windows/macOS/Linux support

  • Hardened math sandbox: AST allowlist for expression evaluation (GHSA-2p69-jpm6-jrxh)

🚧 In Progress

  • verify_json — JSON Schema validation tool

  • verify_finance — NPV/IRR/amortization tool

  • Cursor IDE integration guide

🔮 Planned

  • verify_legal — Deadline and liability verification

  • verify_statistics — Hypothesis test validation

  • SSE (Server-Sent Events) transport for web UIs

  • TypeScript implementation

📁 Examples

See the examples/ folder for:

  • Python client usage

  • Sample verification scripts

  • Integration examples

🛠️ Development

# Clone
git clone https://github.com/QWED-AI/qwed-mcp.git
cd qwed-mcp

# Install with dev dependencies
pip install -e ".[dev]"

# Run tests
pytest tests/ -v

# Format code
black src/

📖 Documentation

Resource

Link

Full Docs

docs.qwedai.com/mcp

Tools Reference

docs.qwedai.com/mcp/tools

Examples

docs.qwedai.com/mcp/examples

Troubleshooting

docs.qwedai.com/mcp/troubleshooting

MCP Protocol

modelcontextprotocol.io

🔗 Related Projects

📄 License

Apache 2.0 — See LICENSE

Available Tools

2 tools
execute_python_codeA

Executes Python code in a subprocess with restricted environment variables. Note: This runs with server privileges; ensure inputs are trusted.

ParametersJSON Schema
NameRequiredDescriptionDefault
codeYesThe Python code to execute.
backgroundNoExecute asynchronously in the background and return a tracking job_id. Set to True for heavy logic verifications.

TDQS

A3.8/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses restricted environment and server privileges, which are important for safety. However, without annotations, it lacks details on specific restrictions, side effects, or error handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences: one for core action, one for important caution. No extraneous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Lacks description of return values or output format, especially important since no output schema is provided. Does not explain error behavior or what happens in synchronous vs asynchronous execution.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Both parameters are fully described in the schema (100% coverage). The tool description does not add much beyond the schema, but it reinforces the background parameter's purpose for async tasks.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool executes Python code in a subprocess with restricted environment variables. It distinguishes itself from the sibling tool 'verification_status' by implying that background execution returns a job_id for status checking.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides a security caution about server privileges and trusted inputs. The background parameter description advises using it for heavy logic verifications, linking to the sibling tool for status checks.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

verification_statusB

Check the execution status and output of a background verification task.

ParametersJSON Schema
NameRequiredDescriptionDefault
job_idYesThe UUID returned by execute_python_code when background=True.

TDQS

B3.4/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, and the description only states a read operation without detailing behavior on invalid job_id, output format, or safety of repeated calls.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence with zero waste, directly stating the tool's purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description lacks details on output structure, possible status values, error handling, or pagination, leaving the agent underinformed for a status check tool with no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description covers the job_id parameter fully; tool description adds no additional meaning beyond the schema, so baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Check the execution status and output of a background verification task' uses a specific verb ('check') and resource ('execution status and output of a background verification task'), clearly distinguishing it from sibling tool execute_python_code.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use after executing a background task, but lacks explicit guidance on when to use vs alternatives, scenarios to avoid, or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 2 tool updatesv0.2.0
    • First observedexecute_python_code
    • First observedverification_status
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TDQS

B3.4/5.0
Disambiguation5/5

The two tools have clearly distinct purposes: one executes Python code, the other checks the status of a background task. There is no overlap in functionality.

Naming Consistency4/5

Both tools use snake_case, but one follows a verb_noun pattern (execute_python_code) while the other is noun_noun (verification_status). Slight inconsistency but still readable.

Tool Count2/5

With only 2 tools, the server feels very sparse for any meaningful functionality. A code execution server would typically need more tools for environment management, file I/O, etc.

Completeness2/5

The tool set lacks essential operations for a code execution server, such as managing environments, reading files, or handling dependencies. Only bare minimum provided.

Maintenance

ActivityMaintained
ResponsivenessSlow

Resources

Unclaimed servers have limited discoverability.

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If you are the server author, to access and configure the admin panel.

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