"A clean web agent named x402-cleanweb-agent" matching MCP servers:

Codebase Q&A agent with git-history awareness. Explore a repo with list_files, read_file, and search, plus git log, blame, and diff and a repo map to answer "why did this change?" questions. Runs locally as an MCP server for Claude Code and other MCP clients.

Lets any MCP client call SWARM's live services — GitHub code-health scans, researched summaries and reports, and everyday utilities — paying per call in USDC on Base with no account or API key. Payments are metered by a spend cap and only settled after the work succeeds.

Lets any MCP-capable AI coding harness route code reviews and codebase questions through DeepSeek's web chat, exposing review, ask, and status tools with read-only repository access by default.

MCP server that keeps language server sessions warm and routes multiple languages through one process. Agents get persistent cross-file awareness, speculative execution (simulate edits before writing to disk), and 20 skills that encode correct multi-step operations like safe rename, blast-radius analysis, and end-to-end refactoring. Single Go binary, no runtime dependencies.

A TypeScript-aware MCP server that provides coding agents with repository discovery, code intelligence, and web project context for local codebases. It enables deep symbol navigation, diagnostic reporting, and structural analysis of monorepos without requiring full IDE integration.

Enables AI coding agents to review Swift code, scaffold new iOS apps, and build, test, and preview them in the Xcode Simulator using local Apple guides and source references.

Provides tools for managing tasks, searching docs, and running a heuristic quality gate to check agent output for common issues before human review.

Enables AI coding agents to query a fully local SQLite FTS5 memory index of a codebase, returning high-density identity cards with exact line references, AST symbol contracts, phase maps, and colloquial intent search so agents can work without scanning raw files. It also supports incrementally syncing code changes and enriching knowledge under a six-pillar quality gate, keeping everything on-device with no cloud leakage.

Builds, validates, and render-tests Panzoid Shader Object JSON in a real WebGL 1 Chromium context, exposing these capabilities as MCP tools.

An OpenAI-powered developer intelligence MCP server that scans GitHub repositories, extracts and clusters agent engineering patterns, analyzes local codebases, and proposes safe AGENTS.md improvements.

Enables MCP-speaking AI research agents to coordinate plans, tasks, experiment runs, and claims on a shared evidence board, tracing each claim to the code that produced it and flagging results that need rechecking when dependencies change.

MCP bridge from OpenCode to Cursor agent CLI, enabling code review, debugging, and planning via Cursor cloud.

Enables multi-agent code review with P0/P1/P2 severity scoring by orchestrating locally installed AI CLIs (Claude, Codex) to perform parallel analysis, deterministic scoring, and consensus-building on git diffs.

MCP server that runs a unified mission across multiple read-only senses (repo, net, browser) and returns a claim graph with verdicts, contradictions, and next-step probes.

MCP server that guides an AI agent through stack trace triage, from raw error to the commit and PR that introduced it.

Enables AI coding agents to query a locally indexed codebase graph for symbol definitions, immediate callers and callees, and multi-hop downstream dependency impact analysis through MCP tools.

Provides a code-quality backend MCP tool that automatically writes and repairs pytest tests, runs them in a sandbox, validates their effectiveness via mutation testing, and surfaces suspected source bugs for human review.

An AI-powered code review agent that leverages Model Context Protocol (MCP) and Claude to provide intelligent, context-aware code reviews.

A token-efficient, codebase-aware AI agent runtime that provides MCP tools for starting runs, getting run states, explaining code, and finding files.

Bridges UI feedback captured by a browser extension on localhost apps into a Claude Code session, queueing picked elements, comments and rewrite requests as batches that the coding agent can claim and act on. It also lets Claude report progress and per-item results back to the extension, and can import batches exported as JSON.