"Information on agent swarm architecture" matching MCP servers:

Compare evidence-linked documentation claims with facts observed in the current source tree.

An MCP server that extends AI coding assistants with deterministic, algorithmic capabilities such as code analysis, fault localization, and formal verification, enabling an autonomous engineering team within the IDE.

Enables scanning Java/Maven projects to generate TOGAF-standard architecture deliverables (Excel and PPTX) via natural language commands.

Analyzes Java Spring Boot Maven repositories by scanning source code, building a dependency graph, and exposing tools for architecture overview, change impact, dependency cycles, rule validation, and refactoring targets so LLMs can answer architecture questions without rereading the codebase.

Analyzes GitHub and local repositories to automatically generate visual architectural diagrams such as dependency graphs, class diagrams, and data flow diagrams.

An MCP server that exposes Swarm's fact reconciliation to AI agents, allowing them to query scope, evidence gaps, and review requirements without being able to issue a final verdict.

An MCP server for evaluating C# project architecture quality using the Modularity Maturity Index (MMI) framework. It provides tools for detecting layering violations, circular dependencies, and encapsulation issues with interactive D3.js visualizations.

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.

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.

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

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.

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.

Enables AI agents to access live VS Code editor state, symbol navigation, diagnostics, and language-aware editing through MCP, bridging the gap between what the agent can infer from disk and what the editor actually knows.

Provides AI coding agents with an embedded knowledge graph and architecture governance tools, enabling blast radius analysis, compliance checks, and smart context extraction from codebases.

A local-first, auditable code review MCP server that freezes Git changes, creates immutable ReviewBundles, provides role-isolated contexts for correctness, security, architecture, and test reviewers, validates structured findings, and generates deterministic JSON/Markdown reports.

MCP server enabling AI assistants to understand GitLab repositories through on-demand source code analysis using specialized AI agents.

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.