"KiCad MCP (Model Context Protocol) integration" matching MCP servers:

A read-only MCP server for AI agents to understand KiCad projects through progressive disclosure, providing compact summaries and drill-down tools for components, nets, traces, and ERC/DRC checks without blowing context budgets.

Enables MCP-compatible assistants to inspect and edit the open PCB in KiCad, including reading board info, footprints, nets, tracks, selection, and BOM data, as well as moving footprints, adding tracks and text, updating BOM fields, and saving the board.

MCP server for KiCad 10 that provides live PCB access, file-based schematic handling, symbol search, schematic generation from pinouts, and a Python scripting escape hatch.

MCP server that analyzes, reviews, and exports KiCad 9 designs, with live board editing via IPC and a built-in design-review engine.

AI-powered MCP server for KiCad that enables creating and modifying schematics, searching components, managing hierarchical projects, generating PCB placement, routing boards locally, and creating copper pours through natural language.

Enables creating and editing KiCad projects through natural language, including scaffolding projects, placing schematic symbols, wires and labels, and adding PCB footprints, tracks and nets. It also runs ERC/DRC checks and exports to PDF, SVG, netlist, BOM, STEP, DXF, gerbers and drill files via kicad-cli.

Enables coding agents to query KiCad project data (components, nets, measurements, DRC/ERC, BOM, renders) and edit open boards live via KiCad's IPC API.

Provides schematic/PCB analysis, authoring, and SPICE simulation through MCP, enabling direct KiCad file manipulation and verification without requiring KiCad for reading.

Enables LLM agents to operate on KiCad by reading compressed schematics (TOON format), executing atomic tools, and updating context via delta and local area.

MCP server exposing KiCad PCB Editor functionality via IPC API.

Enables automated KiCad-adjacent workflows by parsing and round-tripping S-expression files, classifying DRC/ERC reports, and generating pin-header footprints without a running KiCad instance.

Enables MCP clients such as Claude Code to work on KiCad 10 designs by driving kicad-cli for ERC, DRC, netlists and fabrication exports, KiCad's IPC API for live board editing, and lossless edits of schematic and project files. It also provides design review, routing, parts and datasheet tooling so a board can be treated as data and checked against fab limits.

MCP servers for KiCad schematic, PCB, symbol, footprint, and project automation, enabling AI-assisted electronic design via tools for read/write, analysis, and exports.

Enables KiCad CLI automation via MCP, providing tools for ERC, DRC, BOM export, netlist export, Gerbers, drill files, STEP, IPC-2581, and GLB output.

An MCP server that enables AI assistants to analyze schematics, inspect PCBs, trace connections, validate designs, and generate embedded code for KiCad projects.

Enables LLMs to inspect, edit, analyze, and render PCB layouts in real-time using the KiCad IPC API, providing tools for board configuration, footprints, tracks, zones, nets, text, shapes, dimensions, exports, screenshots, and CLI automation.

AI-powered PCB and schematic design with KiCad. Works with Claude, Cursor, VS Code, Claude Code, and any MCP-compatible client.

An MCP server that seats multiple LLMs as a council, letting your assistant query them in parallel or in sequence, relay answers for cross-critique, and merge conclusions within one conversation.

MCP server that pings 130+ free coding LLM models across 17 providers in real-time, ranks them by latency, and helps AI agents pick the fastest available model.

Trust, identity, and reputation infrastructure for AI agents. Register agents with W3C DID (Ed25519), check EigenTrust reputation scores, submit peer attestations, search agents by capability, and verify IPFS-anchored audit trails. 11 tools.

An MCP server that provides AI trading agents with persistent, outcome-weighted memory to learn from historical performance and detect behavioral biases. It enables agents to automatically adjust strategies and optimize position sizing based on context-aware recall of past trade outcomes.

Connects to wetlab protocol resources such as protocols.io, enabling users to access and manage experimental protocols via natural language.

Enables playing a Workato-themed text-based RPG through MCP tools, allowing users to explore dungeons, battle enemies, and manage character progression in an integration-themed adventure.

Enables AI assistants to directly manage Anki flashcards, decks, notetypes, tags, and media, with support for batch operations, searches, and deck exports via file-based input/output.

Enables AI agents to create and edit real KiCad schematics and projects, run ERC/DRC validation, generate BOMs, and produce schematic/PCB/3D renders via kicad-cli, with SKiDL support and automatic backups.

A comprehensive MCP server for managing AI-assisted Dungeons & Dragons campaigns, featuring tools for character sheets, combat tracking, and world-building. It enables players and DMs to interact with 5e game mechanics and query personal PDF rulebooks using RAG capabilities.

Enables AI assistants to interact with KiCAD for PCB design automation, including schematic editing, component placement, routing, DRC/ERC, and export.

Open-source MCP server for Autodesk Revit 2022 to 2027: read, audit and edit live models with 89 tools, one Undo entry per change, and a workstation read-only lock.

An MCP server that turns the Hugging Face Hub into a conversational model picker with a tool-use eval harness to prove the agent actually uses it correctly.

An MCP server that keeps raw tool output out of the context window by sandboxing and compressing results (about 98% reduction), persisting file edits, git operations, tasks and decisions in SQLite with BM25 retrieval so the agent resumes after compaction, and enforcing routing across 17 platforms via MCP and hooks. It also encourages the model to write scripts that compute answers and log only results instead of reading large data into context.

Multi-modal RAG engine for AI assistants. Stores conversation history, conclusions, diffs, error traces, and other development artifacts in LanceDB with vector search, multi-factor scoring, and an LLM-driven consolidation pipeline.

Context Mode is an MCP server that reduces context window waste by sandboxing data-heavy tools, tracking session state in SQLite, and promoting code-based analysis over raw data reads, achieving up to 98% context savings.

An MCP server that preserves LLM context by intercepting large data outputs and returning only concise summaries or relevant sections. It enables efficient sandboxed code execution, file processing, and documentation indexing across multiple programming languages and authenticated CLIs.

Enables agents to query governed metrics through MCP, including describing metrics, running deterministic SQL against a warehouse, explaining join path preferences, and searching semantically ambiguous terms.

Provides official INDEC register designs and methodological rules to AI models, enabling accurate EPH data analysis code (R/Python) without hallucinations.

Local-first shared memory and coordination layer for AI coding agents, with repository evidence, reservations, handoffs, code graph context, and dashboard review backed by PostgreSQL/pgvector.

Persistent 3D/2D spatial world model MCP server for AI agents. Entity tracking, object permanence, AABB collision simulation & view frustum projection via local SQLite.

Enables querying Odoo's model registry (fields, inheritance, methods) without a database connection by loading the registry in-memory.

keeps the rules, decisions, and proof-of-work an agent needs in front of it

A local-first MCP server that ingests PDFs, extracts structure, and provides semantic search and sequential navigation tools for AI clients to query and learn from documents.