"Agent File Control MCP Server" matching MCP servers:

Enables AI coding agents to design, analyze, and evaluate agent system designs against a curated catalog of agent patterns, with retrieval, scoring, and refinement workflows.

A TypeScript stdio MCP server that lets agents read, import, propose connections for, and apply optimistic patches to versioned agent-draw diagram documents.

Mneme exposes a governed Decision Index so MCP clients can propose candidate architectural decisions and query decision state, applicability, and traceability. Proposals remain non-authoritative: accepting or activating protections stays under explicit human control.

Enables coding agents to write repository documents (READMEs, RFCs, design docs, ADRs) from verified codebase facts, using a separate model for drafting and agent fact-checking for accuracy.

Enables generating, reading, auditing, and previewing BPMN 2.0 diagrams for Bizagi Modeler, with an automatic layout engine that produces files Bizagi can open, plus optional control of the Bizagi Modeler desktop app on Windows.

AI-native architecture diagramming for MCP clients (Claude Code, Cursor, Windsurf). The calling agent authors the graph (nodes, groups, edges); Flowgraf validates it, lays it out deterministically with ELK, renders an SVG + Mermaid, and returns a link to a live, editable canvas you can refine by chat, drag, or one-click AI design review. Agent-authored ops — no API key and no LLM cost to the calle

Enables AI coding agents to retrieve mode and stage guidance so they can lead users through a 9-stage design workflow, including questions, required artifacts, exit criteria, dependencies, pitfalls, rollback impact, and environment requirements. It helps non-designers turn ideas into buildable HTML/WPF design specs while keeping the human in control of confirmation and revisions.

Enables two coding agents to deliberate on a plan in a shared room, taking turns to argue and converge until the lead writes a spec file and closes the room.

Analyzes a local codebase and exposes its structure, per-file summaries, dependency graph, and complexity hotspots as tools for MCP clients like Claude.

Compiles 10 languages into a local AST and Stack Graphs relational index, exposing 12 MCP tools for sub-50ms blast-radius, centrality, and pathfinding queries that cut agent context token burn by ~85%. It also enforces architectural compliance through in-memory Virtual AST workspaces, embedded Datalog policy proofs, zero-config Louvain modularity (ΔQ) gates, and post-edit scope-creep audits.

Stop pasting your file tree into Claude. Give any AI assistant real architectural understanding of a codebase — local, private, zero‑config.

Enables assistants to turn a plain-language process description into a checked BPMN swimlane diagram, asking only for missing details and showing a picture for approval. Once approved, it exports the diagram as SVG, PNG and a .bpmn file that opens in Camunda, all drawn and checked locally on the user's own computer.

MCP server for Umtri — give your AI coding agent a persistent map of your project's structure, dependencies, and bugs.

Enables Claude Desktop and Claude Code to build, update, inspect, validate and compile workflows for the SOLVE-IT Workflow Builder from natural language, automatically laying out nodes and connections and checking them against the SOLVE-IT knowledge base. Each result is written as a JSON file for import into the builder, or returned as a share link when small enough.

Enables AI assistants to directly control Autodesk 3ds Max through natural language to create models, set materials, adjust lighting, and automate animations. It bridges the Model Context Protocol with 3ds Max via a TCP socket to execute Python and MAXScript commands.

Generates editable Excalidraw diagrams from natural language system descriptions, with properly bound arrows and labels. Includes tools for diagram creation, validation, and backend status.

Gives terminal coding agents a local browser canvas for rendering charts, tables, metrics, markdown, live widgets and sandboxed MCP App UIs that would otherwise reach them as raw JSON. Lets agents pose blocking visual multiple-choice questions and read back the user's clicks, selections and an animated architecture map of file activity.

Turns messy operational documents, SOPs, incident playbooks, spreadsheets, and business communications into faithful, source-grounded visual workflows directly inside Claude Desktop, Cursor, Zed, Windsurf, or any MCP-compatible agent. It also supports revising existing workflow graphs while preserving citation integrity and retrieving stored visual artifacts by ID.

Enables analysis of any GitHub repository to get architecture, file roles, execution flows, system design Q\&A, and structured agent context. Works with MCP-compatible clients like Claude Desktop, Cursor, and Windsurf.

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.

Exposes the Polaris architectural fitness-function control plane's REST API as grouped MCP tools over stdio, letting agents manage tribes, squads, fitness targets and functions, measurement sources, submissions, evaluations, waivers, insights, and events. Handles Google OIDC login and silent token refresh automatically, and submits measurements with an ingest API key.

Exposes read-only Huly task intake, architecture guidance, UX patterns, and static validators through eight MCP tools, letting host agents drive approval-gated Flutter and Frappe delivery workflows. It can also be inspected directly (e.g. via the MCP inspector) so users can exercise the tools without an agent.

Enables MCP clients to list, select, create, summarize, and edit ExcaliDash (Excalidraw) drawings through the Drawing Agent API, supporting both stdio and Streamable HTTP transport.

Enables an AI agent to join a live Excalidraw collaboration room as a headless participant, read the drawing in real time, and add or modify elements on the shared canvas.

Enables a coding agent to sketch explanations step by step on a shared hand-drawn canvas beside the chat, highlighting parts as it talks and reading back anything the user draws or notes. Boards persist per chat and can be searched, saved, and exported as Excalidraw files or PNGs.

Infers the architecture rules a TypeScript repo already follows from its import graph, with the evidence for each rule. Read-only tools to scan, recommend and explain rules, so an agent can check them before writing code.

A comprehensive bridge connecting AI agents to Unreal Engine 5.7 through 39 MCP tools for scene manipulation, asset management, and blueprint control. It enables real-time perception and editor automation using the Remote Control API and file-based protocols.

Enables an AI assistant to load, query and edit a YAML or JSON graph file, with tools for adding, editing and removing nodes and edges, managing reusable styles and graph-level properties, and saving changes. Every change is written to the file immediately, so the same graph can be viewed and edited live in the companion web app.

An architecture consulting server that reviews multi-agent systems against a knowledge graph of patterns derived from expert literature. It provides grounded recommendations with chapter citations, maturity scoring, and interactive architecture diagrams to identify and fix structural gaps.

This MCP server enables AI models to analyze local Python codebases using abstract syntax trees, providing tools for file structure analysis, symbol search, import graphing, docstring auditing, and refactoring prompts without loading entire source files into context.