Read source code files from a repository for code review, debugging, and understanding implementation details.
MIT
622,980 tools. Updated 2026-09-29 23:33
"Understanding Code Execution" matching MCP tools:
- View disassembly at a specific address or current program counter, with source code interleaved for understanding CPU execution.MIT
- Determines if understanding meets 95% threshold; otherwise code edits remain blocked.MIT
- Annotates source files to show executed lines and loop iteration counts, enabling understanding of code paths and branches run during debugging.-
- Trace code execution flow or map structural dependencies to analyze method calls, call chains, and architecture.-
- Analyze and trace code execution paths with semantic understanding, identifying data flows and dependencies to debug complex distributed systems efficiently.MIT
Matching MCP Servers
- AlicenseAqualityDmaintenanceExecutes Python code in isolated rootless containers while proxying MCP server tools, reducing context overhead by 95%+ and enabling complex multi-tool workflows through sandboxed code execution.1341GPL 3.0
- AlicenseAqualityAmaintenanceProvides a sandboxed Docker environment for executing Python code against API endpoints, exposing tools for discovery, inspection, execution, and reuse.1111MIT
Matching MCP Connectors
- execution-market-mcpOAuth
Execution Market is the Universal Execution Layer — infrastructure that converts AI intent into physical action. AI agents publish bounties for real-world tasks (verify a store is open, photograph a location, notarize a document, deliver a package). Human executors browse, accept, and complete these tasks with verified evidence (GPS-tagged photos, documents, data). Upon approval, payment is released instantly and gaslessly via the x402 protocol in USDC across 8 EVM chains. Key cap
Code mode (preview): the AI writes a script against a typed foundry.* API and runs it in a sandbox.
- List execution providers and their capabilities to choose a suitable backend for running code. Provides machine-readable details on each provider's readiness and strictness.Apache 2.0
- Add a new cell to CodeBook for code execution, documentation, AI processing, data management, or visualization within Circuitry's workflow platform.-
- Check pending code actions against governance rules to return an allow or consult_required verdict before execution.Apache 2.0
- Set a debugger breakpoint at a specific line to pause execution and inspect code paths. Requires an active tab and loaded script.MIT
- Retrieves task prompts with descriptions and technical data from Webvizio MCP Server to facilitate proper understanding and execution of development tasks when provided with a task UUID.MIT
- Retrieve generated DS2 execution code for a decision flow by supplying its UUID. Use it to review or debug the exact SAS logic before running.Apache 2.0
- Generate or modify code files with smart diffs. Provide file path and detailed prompt to create or edit files using context for accurate code generation.MIT
- Run SAS programs asynchronously by submitting code to the Job Execution service for later retrieval of logs and output.Apache 2.0Destructive
- Identify uncalled functions (dead code) in Solidity contracts to clean up unused code or improve code coverage. Supports filtering by entry points, inherited functions, and test frameworks.AGPL 3.0
- Fetch and analyze smart contract source code and execution behavior to understand contract logic and on-chain activity for risk assessment.AGPL 3.0
- Retrieve the active Python execution environment for new code cells in Circuitry's visual workflow platform.-
- Execute supplied local Playwright code or a local test file. This is a code-execution and artifact-writing boundary: qmax-mcp first requires an MCP human-approval elicitation bound to the exact test digest.MITDestructive
- Ask questions that require Python code execution for calculations or data analysis, using Groq compound models to generate and run code in real time.MIT
- Retrieve the current notebook state to understand cell order, selected cell, and execution status for context-aware coding workflows.-
- Configure Python code execution environment for new cells by specifying target runtime like pyodide, local computer, or remote server.-