"A map or mapping service" matching MCP servers:

MCP server that provides a live, terminal-native layered dependency map for AI coding assistants, with tools to track and visualize development progress in real time.

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

Enables scanning repositories for hardcoded service URLs and clients, and building service-to-service API dependency maps.

Automatically generates mind map images from text content using Coze API workflow. Returns accessible image links that can be used in MCP-compatible tools like CodeBuddy, Cursor, and Qoder.

Point an agent at a codebase: narrowed-scope architecture map, dependency/EOL risk list, modernization estimate inputs.

Enables MCP clients such as Claude Code, ChatGPT desktop Codex mode and Codex CLI to declare and maintain a live, terminal-native layered dependency map of a system as it is built. Exposes tools that lay down a ghost design first, mark the node currently under construction, and light nodes solid only when they are built and verified.

Static codebase analysis as MCP tools — give AI coding agents a map of your repo instead of letting them burn half their tokens rediscovering it file by file.

Converts Mermaid flowchart syntax or a plain indented outline into a shareable diagram link and an editable board in a browser-based editor, returning read-only and editable URLs plus node and connection counts. Also lists built-in templates such as swimlane, decision tree, org chart, network, and mind map diagrams.

Enables coding agents to navigate and score brownfield multi-service flows by mapping use-case trees, tracing loadouts and consumers, and detecting drift.

Enables coding agents to declare an entire system design up front as ghost nodes, then light each node up as it is built and test-verified, exposing a live layered dependency graph in a terminal pane beside the conversation. Structural corruption such as upward-pointing edges is refused, while progress and broken foundations stay visible through eight mmap_* tools.

A Model Context Protocol server for deep codebase understanding of Python projects, focusing on data analysis and scientific computing. It provides architectural analysis, pattern detection, dependency mapping, test coverage analysis, and AI-optimized context generation.

Exposes eight mmap_* tools that let a coding agent declare a whole layered dependency design as ghost nodes, then light nodes through building and verification while a live terminal pane shows the map. The server also tracks status such as in-progress spinners, verified-green nodes, and red cracked foundations.

Enables an AI coding agent to publish a live, layered dependency map of a system under construction: it ghosts the intended structure first, then lights nodes up as they are built and verified. A terminal pane beside the conversation keeps that map visible, showing what is being worked on now and flagging when later changes crack a foundation beneath it.

Enables AI coding agents to declare and maintain a live, layered dependency map during bottom-up development, exposing eight mmap_* tools that ghost the intended design first and then light nodes up as they are built and verified in a terminal pane beside the conversation.

Publishes eight tools that let an AI coding agent declare an entire layered dependency design as ghost nodes before writing code, then light each node up as it is built and verified—with a spinner on the current node and reddening when later work cracks a foundation. This gives developers a live, terminal-side view of bottom-up progress where upward edges and duplicate ranks are refused, so a bad design can be vetoed while it is still only a picture.

An MCP server that lets Claude Code, Codex, pi, omp and other MCP clients declare and maintain a live layered dependency map of a system, exposing eight mmap_* tools to add ghost nodes, draw downward-only edges, and light nodes up as built and verified. It turns bottom-up progress into a shared ledger in a terminal pane beside the conversation, marking nodes red when later work cracks a foundation.

Enables coding agents to declare a layered dependency map as ghost nodes and then light nodes up as they are built and verified, with a live terminal pane and eight tools for tracking structure during bottom-up development. It keeps edges pointing downward, shows what is being worked on with a spinner, and marks cracked foundations red.

Enables coding agents to publish a layered dependency map of a system as ghost nodes, then light each node up as it is built and verified, with cracks and faults propagating visibly to upper layers. It exposes tools for declaring ranks, edges and evidence so a terminal pane beside the session always shows current structure and progress.

Enables cross-repository architecture discovery and dependency routing across multi-service codebases, with automated scanning and batch AST indexing for AI agents to trace request lifecycles and navigate service boundaries.

Enables Claude Code, Codex, and other MCP clients to declare a layered, bottom-up dependency design as ghost nodes and then light each node up as it is built and verified, mirroring the whole structure in a live terminal pane beside the conversation. It exposes a set of mapping tools that record nodes, downward-only edges, in-progress attention, and test evidence, refusing only structurally invalid updates.

Enables agents to generate a JSON sitemap of how a path through a TypeScript/JavaScript codebase runs, capturing the summary, areas, every step with its file, lines, description, calls and data, and the links between services. The resulting document can be opened in a viewer that draws the same map as a single page, and rebuilt in CI to keep system documentation current.

Enables MCP-compatible AI agents to read and write architecture-map projects and diagrams with per-project access controls via OAuth 2.1/PKCE.

Gives an AI coding agent tools to declare and maintain a live, layered dependency map in a terminal pane beside the conversation: ghost nodes for the intended design, a spinner on what is being built, and solid green only for what is built and verified. Structural rules keep dependency edges pointing downward and make cracks in a foundation visible as red nodes.

Converts quantum circuits into ZX-diagrams using categorical quantum mechanics, enabling circuit visualization, analysis, and optimization through deterministic gate mapping and rewrite rules.

Schema Validator AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Enables coding agents to declare a whole system as a layered dependency map of ghost nodes before any code, then light each node up—spinner while under construction, solid green once verified by a passing test run, red if later work cracks its foundation—so progress is shown as a live bottom-up picture beside the conversation.

Exposes eight mmap_* tools that let an MCP client declare a layered dependency design as ghost nodes, then light each node up as it is built and verified, so progress is visible as a live map in a terminal pane. Edges may only point downward, and a node turns solid green only with evidence, turning red if later work cracks a foundation.

A knowledge graph MCP server for Moleculer and Go microservice projects that scans codebases, extracts service metadata, seeds Neo4j, and exposes tools for LLM clients to query and understand service architecture.

Validates and renders declarative JSON diagram specs to themeable SVG. The format has no coordinates, so a model writes structure and the renderer does the layout; tools: validate, render, kinds.

Generates GCP architecture diagrams, sequence diagrams, flow charts, and class diagrams using Python diagrams DSL via MCP.