"Hive" matching MCP servers:

Context infrastructure for AI-assisted development — on-demand Obsidian vault access via MCP

Enables shared, persistent memory and coordination for Claude Code and Codex sessions through a visible crew of tmux workers and a local SQLite store.

Enables Claude Code agents and sub-agents to share a persistent, compiled memory of project state, decisions, tasks, and facts across sessions instead of re-reading transcripts. Provides token-efficient bootstrap, search, commit, leased task claiming, and task-specific context compilation so parallel agents can coordinate without clobbering each other.

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

Enables AI assistants to read and edit a spatial canvas board of notes, tasks and ideas through the running desktop app, creating, updating, linking, grouping and arranging nodes, importing files, focusing the view and undoing changes so edits appear instantly and stay reversible.

Enables coding agents to record, recall, supersede, and trace temporal decisions with rationale using MCP tools.

MCP server for personal and shared memory with full-text search (SQLite FTS5) and outcome tracking, compatible with any MCP agent like Claude Code, Cursor, and Codex CLI.

An MCP server for multi-agent collaboration, providing team messaging and long-term semantic memory with trust-based access control and single-writer consistency.

Enables AI agents to search and modify a personal knowledge base through OAuth-secured MCP tools, covering Obsidian vaults and Google Drive mirrors with semantic search, note read/write operations, audit logging, and eval-gated local classification.

An MCP server enabling AI agents to record, query, and share structured problem-solving experiences with human review and confidence decay.

Provides AI coding agents with persistent, graph-connected memory across projects, enabling cross-project context retrieval via synaptic connections and hybrid search.

Persistent memory graph, knowledge marketplace, and MCP tool gateway for autonomous AI agents. Agents store experiences, trade knowledge via micropayments, and discover capabilities across the Hive network.

Local-first personal memory for AI agents. Ships its own SQLite memory store, so it runs standalone: agents propose and recall confirmed memory, while only the human can confirm, from a separate CLI. Optionally uses the macOS Hive app for encrypted vaults. Also provides a shared board for coordinating several agents.

Enforces team knowledge and workflow policies for AI coding agents by providing context, decisions, and gates before code changes are made.

Enables AI agents to contribute and search a shared knowledge commons, so that solutions learned by one agent become available to all connected agents.

Provides access to a community knowledge base of 16k+ debugging solutions and 223+ reusable skills, plus auto-scanned project-specific knowledge bases that learn and store solutions as you work.

A Claude Code plugin that runs a cheap, always-on model as an MCP server to accumulate knowledge of your codebase, so your agent can ask broad questions instead of re-reading files.

MCP server for temporal state queries and cryptographic audit trails. Query historical entity state at any point in time, generate Merkle proofs of past state, and anchor contract snapshots for immutable provenance.

Enables teams of coding agents to share one live plan synced through their existing git remote, so each agent receives teammates' contract, decision, and task changes at its next tool call. Provides tools for publishing contracts, logging decisions, adding and claiming tasks, and reviewing the plan for contradictions.

Enables teams of AI coding agents (Claude Code, Cursor, Codex) to share persistent, time-aware graph memory and coordinate their work via MCP, so agents recall verified fixes at the moment of failure, learn procedures automatically, avoid file conflicts, claim tasks race-free, and hand off facts and decisions between sessions.