"Two agents working simultaneously" matching MCP servers:

Coordination layer for AI coding agents working on the same codebase. Adds file locks, shared project memory, and cross-machine file sync so Claude Code, Cursor, Windsurf, and other MCP agents stop overwriting each other.

Enables agents to reduce tool noise by exposing only two meta-tools for searching downstream MCP servers and calling their tools on demand. Connections are lazy and tool lists are cached, so configured servers can be used without loading every tool upfront.

Enables AI agents to maintain Git-backed long-term project memory over MCP, supporting on-demand retrieval, curated writes, conflict-safe versioning, idempotency, and crash recovery so new sessions or machines can recover context and continue working.

Converts URL content to Markdown, providing two tools: one for extracting main article content and one for converting the entire HTML.

Records your terminal sessions per command (PTY + OSC 133) into local SQLite, so AI agents can search, retrieve, and diff what commands actually printed. Secret redaction is applied by default to everything served over MCP.

Infrastructure access broker for AI agents — SSH & Kubernetes. Per-operation ephemeral credentials minted by a separate signer; the model never touches one. MCP stdio / HTTP+OIDC.

Turn any OpenAPI/Swagger/Postman spec into an MCP server — give your LLM live access to any API.

Your agents, briefed. Not flooded. Self-hosted context compiler: git-backed team knowledge served to coding agents as token-budgeted bundles over MCP.

An MCP server that gives AI agents persistent, narrative memory: concepts as nodes, relationships as typed "because" edges, so anything filed can be pulled back by association rather than by address.

Radar is an open-source Kubernetes observability and diagnostics MCP server. It exposes cluster health, workload diagnosis, logs, events, topology, audit findings, and remediation actions to AI agents through the Model Context Protocol.

Local CI/CD engine for AI agents. ActionD listens to LGH git events and runs plugin jobs (Go/Python/Java/web toolchains) in isolated checkouts, with structured results, root-cause failure diagnosis, approval gates, and auto-rollback. The MCP server exposes 23 tools, including dev_cycle_run (commit → CI → structured verdict in one call) and actiond_diagnose for failed-job analysis.

Local, searchable project memory for AI coding agents. Markdown source of truth, MCP interface, safe structured updates

Self-hostable, markdown-native team wiki with a built-in MCP server: agents search, read, and write your wiki pages (ranked Postgres full-text + semantic search, backlink traversal). Plus Atlas, which auto-generates a cited, coverage-checked wiki from your git repos and Jira.

Local-first Git hosting for AI coding agents. lgh serve turns any directory into an HTTP Git remote (127.0.0.1:9418) with push events, commit-status reporting, smart .gitignore generation, secret/large-file detection, and optional LAN sharing with auth. The MCP server exposes 10 tools covering repo registration, one-command backup (lgh up), server control, and event access.

Coordination for parallel coding agents: TTL file claims stored in the git common dir (visible across all worktrees), enforcement hooks that block colliding edits, agent presence, handoff notes, and a git-committed lessons knowledge base with BM25 search. Single static Go binary — no server, no database.

Read-only MCP server for Huawei GaussDB (centralized & distributed), built for coding agents. Three-layer write protection, multi-instance config, schema exploration and single-SELECT execution.

The IDE for agents — read by symbol, edit against a revision, validate with your own build, revert. It is a local stdio MCP server for coding agents. It reads code by symbol with tree-sitter and real language servers (Go, Java, Scala, TypeScript, Python, Rust, Ruby), edits against a known revision and returns compiler diagnostics with each edit, runs the repository's own build, test etc.

Self-hosted Go MCP server that crawls documentation sites into local Markdown/JSONL corpora and lets agents read pages, run crawls, check freshness, and diff changes with zero network access at read time. Single static binary, no CGO, Apache-2.0.

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.

Safe write access for AI agents. Stellar Jay is an append-only business fact store: every change is kept, attributed to the agent that made it, and can be undone. Agents record, correct and retract facts, read entities, and reverse a bad run with undo_changes. Self-host with stellarjay-mcp (Go, AGPL) or connect to the hosted AvianSuite server at https://mcp.aviansuite.com/mcp.