Gdb Mcp Server

Created By
yywz1999a year ago
Overview

what is GDB MCP Server?

GDB MCP Server is a Model Context Protocol (MCP) server that supports AI-assisted debugging, allowing AI agents and other tools to interact with GDB through the MCP protocol.

how to use GDB MCP Server?

To use the GDB MCP Server, clone the repository, install the required dependencies, and run the server. You can then use the MCP protocol to interact with GDB.

key features of GDB MCP Server?

  • Discover and attach to existing GDB processes.
  • Communicate with GDB through a terminal window (optimized for iTerm2 on macOS).
  • Support for MCP protocol for AI assistant integration.
  • Intelligent handling of GDB command blocking with automatic interrupt signals.
  • Support for multi-architecture, multi-host, and remote debugging scenarios.
  • Simple function calls for common GDB debugging operations such as setting breakpoints, stepping through code, and examining memory.

use cases of GDB MCP Server?

  1. Assisting developers in debugging applications across different architectures.
  2. Integrating AI tools to enhance debugging efficiency.
  3. Facilitating remote debugging sessions for distributed applications.

FAQ from GDB MCP Server?

  • Can GDB MCP Server work with all GDB versions?

Yes! GDB MCP Server is designed to be compatible with various GDB versions.

  • Is GDB MCP Server free to use?

Yes! GDB MCP Server is open-source and free to use under the MIT license.

  • How can I contribute to GDB MCP Server?

You can contribute by providing feedback, reporting issues, or submitting pull requests on the GitHub repository.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
yywz1999
Star
15
Language
Python
License
MIT license
Tags

Recommend Servers

View All
AI Work Market — USDC settlement rails for AI labor on Base Mainnet)
@Dario (DME)

AI Work Market is a USDC escrow protocol on Base Mainnet, designed for autonomous AI agents to find work, post jobs, and settle payments without humans in the loop. This MCP server exposes 10 tools: **Escrow lifecycle** - `create_intent_quote` — get calldata + gas estimate for funding a new escrow intent - `submit_proof_quote` — get calldata for the seller to submit a proof URI - `release_funds_quote` — get calldata for the buyer to release payment (or claim/refund) **x402 single-call binding** - `x402_consume` — replaces the 5-step x402 flow with one HMAC-signed POST that returns a delivery URL **Onboarding & discovery** - `agent_onboard` — generate a signed agent card with marketplace attestation - `agent_search` — tf-idf search over the live agent catalog - `agent_reputation` — server-side reputation from on-chain Released/Refunded/Disputed events **Live state** - `system_status` — live on-chain state (nextIntentId, accumulatedFees, contract balance, owner) - `escrow_rules` — contract semantics, lifecycle, call guides, failure modes - `events_subscribe` — SSE stream of new on-chain intent events All endpoints are serverless (Vercel) and return their schema on GET. No browser, no wallet UI required for an agent to integrate. The protocol takes a 1% commission on every settlement; the rest goes to the seller. The full AgentCard is at `/.well-known/agent-card.json` (A2A-compatible). The OpenAPI 3.0.3 spec is at `/.well-known/openapi.json` with `components.securitySchemes` (none, hmacX402). `robots.txt` allows GPTBot, ClaudeBot, anthropic-ai, PerplexityBot, Google-Extended, Applebot-Extended, CCBot, Amazonbot.

7 hours ago
Bring your real authenticated browser session to AI coding agents. Local-first MCP server + Chrome MV3 extension. No cloud. No telemetry.
@Cubenest

peek records the user's actual logged-in browser (DOM via rrweb, console events, network metadata, optional response bodies via opt-in Deep capture) through a Chrome MV3 extension. The extension ships events through a native-messaging stdio bridge to a local MCP server (peek-mcp), which persists them to a SQLite database at ~/.peek/sessions.db. AI coding agents (Claude Code, Cursor, Cline, Windsurf) read sessions from the database via 10 MCP tools: Tool What it does list_recent_sessions List recently recorded sessions (id, origin, ts, event count). get_session_summary LLM-readable narrative summary of a session. get_session_console_errors Console errors recorded in a session. get_session_network_errors Failed/notable network requests in a session. get_user_action_before_error Last N user actions before a console error. generate_playwright_repro Generate a runnable Playwright test from a session. get_dom_snapshot Reconstruct the DOM at a given timestamp. query_dom_history Timeline of attribute/text changes for a selector. request_authorization Side-panel consent for write actions (Level 3). execute_action Dispatch a UI action (gated by permission level + destructive blocklist). Why local-first matters Every other "browser session for AI" tool ships to a vendor cloud. peek's SQLite + extension live on the user's machine — no remote endpoints, no telemetry. The privacy policy (docs/peek/PRIVACY_POLICY.md) is the source of truth. Install # 1. Add the MCP server to Claude Code claude mcp add peek -- npx -y @peekdev/mcp # 2. Install the Chrome extension from the Chrome Web Store # (link added once the CWS listing is approved)

a day ago