"Information on agent swarm architecture" matching MCP servers:

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.

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

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

Enables AI assistants to retrieve a project's architecture overview and file structure, auto-detecting monolith or multiproject layouts and exposing module listings to reduce token consumption.

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.

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.

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

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.

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.

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.

Exposes MCP tools that give desktop agents durable two-tier memory with recall and graph traversal, project code intelligence (symbol lookup, impact walking, notes search), and web search with page-to-Markdown conversion. It also runs a local model gateway that routes Anthropic- and OpenAI-shaped traffic across providers with usage accounting.

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.

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.

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.

Enables coding agents to locate the right files and conventions in a Next.js project in a single call, drastically reducing token usage compared to searching.

An MCP server that gives autonomous coding agents deterministic, schema-validated tools for EVM smart contract development — security scanning, gas profiling, compiler diagnostics, and transaction simulation.

Enables AI assistants to perform read-only introspection of Symfony applications, exposing routes, controllers, services, entities, database schema, migrations, logs, and more via MCP tools.

Verify-before-act safety tools for AI coding agents, providing MCP tools to check packages, lockfiles, manifests, and CI workflows for supply chain risks.

Enables users to turn ideas or PRDs into component selections and architecture designs, audit existing projects with static scans, and manage long-running planning/auditing tasks with caching, cancellation, budget tracking, and checkpoint resume via MCP tools.

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 free, read-only server that lets users diagnose production AI-agent risks: it flags over-privileged API keys from permission descriptions, scans code snippets for the signals that prevent duplicate execution, and explains guard patterns such as idempotency keys, approval gates, outboxes, and circuit breakers. It makes no network calls or writes, and rejects inputs that look like real secrets.

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.