"An overview of knowledge graphs and their applications" matching MCP servers:

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.

Plori runs AI agents in Workspaces. A Workspace is a project folder in the cloud. Several agents can work in it at the same time, each on its own copy of the files, and Plori merges their work back into the folder. Every version of the files is kept.

Enables running one Codex CLI task at a time in an isolated temporary folder, returning Codex's answer and a manifest of produced files for manual review and selective copying.

Exposes 31 high-assurance agentic coding skills as MCP tools and resources, enabling AI agents to invoke structured workflows across DISCIPLINE, TECHNIQUE, KNOWLEDGE LAYER, and REFERENCE registers.

A single, queryable source of engineering constraints that coding agents consult at code-generation time, exposed over an MCP server.

Enables AI coding agents to compile, test, run, hot-swap, and debug Java applications incrementally through MCP, providing runtime feedback for verifying code changes.

A local AST and type-aware Go repository context indexer that uses CHA to map symbols, call graphs, dependencies, and architecture patterns. Built for AI coding agents that need to navigate and reason about large Go codebases without reading raw files.

An MCP server that enables Claude to orchestrate multiple autonomous Claude Code agents working in parallel across different projects, with tools to dispatch, monitor, and manage their progress.

Connects AI coding agents to a shared knowledge base by allowing them to search, retrieve, and contribute coding traces. It acts as a protocol adapter for the CommonTrace API, facilitating collaborative knowledge sharing through natural language queries and tool-based interactions.

An MCP server that connects Gemini 2.5 Pro to Claude Code, enabling users to generate detailed implementation plans based on their codebase and receive feedback on code changes.

An MCP server that enables coding agents to run Claude Agent SDK sessions as asynchronous sub-agents, with tools for starting, continuing, and checking status of Claude sessions.

Gives coding agents structural understanding of a codebase: it indexes Java and Python repositories to resolve symbols, call sites with confidence tiers, module dependencies, diff impact, and hotspots. It also ships an eval harness that measures whether this context actually helps an agent.

Enables AI coding assistants to design, synthesize, heal, and export production-ready accessible web applications and design systems in real time with zero build overhead.

An AI-powered toolkit for the M8 mobile development framework that enables automated generation of Vue pages, low-code components, and mock data. It provides real-time code standard validation and a comprehensive UI component knowledge base to streamline development in AI editors.

Enables end-to-end generation, scaffolding, testing, diagnosis, and auditing of Kotlin applications for Android, Compose Multiplatform, Ktor, and Spring Boot through a coordinated team of specialized agents.

Shared knowledge graph for AI coding agents. Search, create, and link verified technical knowledge across 12 node types with trust scoring, demand signals, and auto-provisioning. Install: npx agent-hive-mcp

Provides coding agents with persistent, evidence-backed project memory and knowledge across sessions, using a structured memory tree and local knowledge base.

Enables AI assistants to incrementally build Laravel and Vue.js applications by creating file structures, methods, and code through natural conversation.

Self-hosted coding agent that runs Claude Code or Codex in your own infrastructure and works from Slack. Exposes codebase investigation, file edits, branch and PR creation, allowlisted command execution, CI status and an audit log as MCP tools, keeping every credential behind the tool layer instead of handing it to the model.

One shared project for your team's Claude Code, Codex, Cursor and OpenCode agents: a task board, decisions and handoffs. Everyone keeps their own plan.