AI & MemoryMCP Registrypypi6 toolsA · 83

Memory Hive MCP server

Name: Memory Hive
Author: 330899935

io.github.330899935 · Updated 2d ago

Local-first memory over MCP. Built-in SQLite store; runs standalone. Agents propose; you confirm.

At a glance

Memory Hive is an MCP server in the AI & Memory category. It runs locally over stdio via `uvx memory-hive-mcp`, and needs HIVE_AGENT_TOKEN. It exposes 6 tools, including recall, propose and manage. It scores A (83/100) on the MCP Skills Hub health score as of Oct 27, 2026.

Source

One-click install

VS Code VS Code Insiders Cursor

Opens your editor and pre-fills the config. Your editor will ask before adding it.

How to install Memory Hive in your AI client

Setup for Claude Code, Claude Desktop, Cursor, Codex, Windsurf, Cline and VS Code — copy-paste ready.

How to install Memory Hive in Claude CodeAnthropic's agentic CLI

Add the server

bash

claude mcp add hive-memory -e 'HIVE_AGENT_TOKEN=<HIVE_AGENT_TOKEN>' -- uvx memory-hive-mcp

Fill in your credentials
Replace <HIVE_AGENT_TOKEN> with your real value. Keep secrets out of any config file you commit.
3
Verify it's connected
bash
```
claude mcp list
```
Sharing it with your team?
Add `--scope project` to write it to .mcp.json in the repository root, which you can commit (with the secrets left as environment variables).
Use it in a session
Ask Claude to use the tools this server exposes (e.g. recall, propose, manage). It discovers them automatically.

How to install Memory Hive in Claude DesktopDesktop app (MCP config)

Open your MCP config
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json · Windows: %APPDATA%\Claude\claude_desktop_config.json

Add this server

json

{
  "mcpServers": {
    "hive-memory": {
      "command": "uvx",
      "args": [
        "memory-hive-mcp"
      ],
      "env": {
        "HIVE_AGENT_TOKEN": "<HIVE_AGENT_TOKEN>"
      }
    }
  }
}

Fill in your credentials
Replace <HIVE_AGENT_TOKEN> with your real value. Keep secrets out of any config file you commit.
Restart Claude Desktop
The tools appear under the 🔌 menu once the app reloads.

How to install Memory Hive in CursorAI-first code editor

Create / edit .cursor/mcp.json in your project

json

{
  "mcpServers": {
    "hive-memory": {
      "command": "uvx",
      "args": [
        "memory-hive-mcp"
      ],
      "env": {
        "HIVE_AGENT_TOKEN": "<HIVE_AGENT_TOKEN>"
      }
    }
  }
}

Fill in your credentials
Replace <HIVE_AGENT_TOKEN> with your real value. Keep secrets out of any config file you commit.
Enable it
Cursor Settings → MCP → toggle the server on. Tools become available to the Composer/Agent.

How to install Memory Hive in Codex CLIOpenAI coding agent

Add to ~/.codex/config.toml

toml

[mcp_servers.hive-memory]
command = "uvx"
args = ["memory-hive-mcp"]
env = { HIVE_AGENT_TOKEN = "<HIVE_AGENT_TOKEN>" }

Fill in your credentials
Replace <HIVE_AGENT_TOKEN> with your real value. Keep secrets out of any config file you commit.
Run Codex
Codex loads MCP servers from config.toml on startup and exposes their tools to the agent.

How to install Memory Hive in WindsurfCodeium's agentic IDE

Edit ~/.codeium/windsurf/mcp_config.json

json

{
  "mcpServers": {
    "hive-memory": {
      "command": "uvx",
      "args": [
        "memory-hive-mcp"
      ],
      "env": {
        "HIVE_AGENT_TOKEN": "<HIVE_AGENT_TOKEN>"
      }
    }
  }
}

Fill in your credentials
Replace <HIVE_AGENT_TOKEN> with your real value. Keep secrets out of any config file you commit.
Reload
Windsurf → Cascade → refresh MCP servers. Cascade can now call the tools.

How to install Memory Hive in ClineVS Code autonomous agent

Open Cline → MCP Servers → Configure
Adds to cline_mcp_settings.json.

Add the server

json

{
  "mcpServers": {
    "hive-memory": {
      "command": "uvx",
      "args": [
        "memory-hive-mcp"
      ],
      "env": {
        "HIVE_AGENT_TOKEN": "<HIVE_AGENT_TOKEN>"
      }
    }
  }
}

Fill in your credentials
Replace <HIVE_AGENT_TOKEN> with your real value. Keep secrets out of any config file you commit.

How to install Memory Hive in VS CodeCopilot / MCP support

Create .vscode/mcp.json

json

{
  "servers": {
    "hive-memory": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "memory-hive-mcp"
      ],
      "env": {
        "HIVE_AGENT_TOKEN": "<HIVE_AGENT_TOKEN>"
      }
    }
  }
}

Fill in your credentials
Replace <HIVE_AGENT_TOKEN> with your real value. Keep secrets out of any config file you commit.
Start it
VS Code shows a ▶ Start action above the server entry. Agent mode (Copilot Chat) can then use the tools.

What does Memory Hive need from you?

API key — Access token issued by your own Hive app when the agent is registered. Only needed for calls the app serves.

HIVE_MODEoptionalEnvironment variable
auto (default) asks the Hive app and falls back to the local store only when the app is unreachable; local never touches the network; remote refuses to fall back.
HIVE_DBoptionalEnvironment variable
Path to the local memory database. Defaults to ~/.memory-hive/hive.db. Only used when the local store answers.
HIVE_AGENT_IDoptionalEnvironment variable
Agent id issued by your own Hive app. Only needed for calls the app serves (HIVE_MODE=auto with the app running, or remote). Not required to use the local store.
HIVE_AGENT_TOKENoptionalsecretEnvironment variable
Access token issued by your own Hive app when the agent is registered. Only needed for calls the app serves.
HIVE_MCP_URLoptionalEnvironment variable
Hive app MCP endpoint. Defaults to http://127.0.0.1:8768/mcp

Pass secrets through your shell environment rather than committing them into a config file.

What tools does Memory Hive expose? (6)

Taken from the project's README — the server itself was not queried, so check its docs for the exact schemas.

recallread
proposewrite
manageread/write
get_contextread
saywrite
boardread

What the code can do

Source analysis currently covers npm packages only. This server ships as a Python package, which needs a different parser.

Before you install

Signals gathered from the source repo and package registry — not a safety verdict.

What it can reach

Runs code on your machine — Executes as a local process with your user's permissions, including filesystem access.
Downloads at launch — The package is fetched from its registry each run unless you pin a version.

Client compatibility

Claude Code: NativeClaude Desktop: NativeCursor: NativeCodex CLI: NativeWindsurf: NativeCline: NativeVS Code: Native

Health score

A · 83

Maintenance, adoption, transparency and packaging — not a safety audit. How this is calculated

Maintenance30%not measurable
No commit history available.
Adoption20%not measurable
No usage data available.
Transparency20%75%
3/4: ✓ public source repo, ✗ declared license, ✓ documentation, ✓ discoverable tool list.
Provenance15%75%
Links to its own repository; package linkage unverified.
Packaging15%100%
Publishes a pinned version (0.1.9).

Documentation

Full README

Apiary Memory MCP

Also known as: Apiary Memory · 记忆蜂巢 · Memory Hive · 蜂巢 · apiary-memory on PyPI and io.github.330899935/apiary-memory on the MCP Registry (from v0.2.0) · old names memory-hive-mcp / hive-memory (v0.1.9 and earlier) still install and still work. Not affiliated with hive.com (team collaboration) or the hive-mcp Claude Code plugin.

Local-first personal memory for AI agents, over MCP. Your agents can search what you have confirmed and propose what they think you should keep; only you can confirm it. Everything lives in one file on your own disk, and nothing is sent anywhere.

It runs on its own. A working SQLite memory store ships inside this package — no account, no cloud, no daemon, no dependencies.

bash

pip install apiary-memory

Desktop app, no terminal: download `apiary-memory-0.2.0.mcpb` and double-click it.

Measured on 2026-10-27, on one MacBook with the Hive running locally — script and raw output in `bench/`:

| Measure | Result | | --- | --- | | Search latency | p95 111 ms, p50 76 ms (warm, includes HTTP) | | Retrieval | correct entry in top-5 for 97.5% of 40 trials | | Corpus | 1,303 entries · 2.39 M chars · 45 days, plaintext only |

*Retrieval used each entry's own title as the query — an easy set. It shows the index is complete and ranks correctly on exact terms, not how well it answers a question asked in your own words. Run `bench/bench_search.py` on your own Hive.*

What you get without the app

A complete, if modest, memory server. On a machine with nothing else installed:

| Call | What happens | | --- | --- | | initialize | answered locally, protocol 2024-11-05 | | tools/list | answered locally, six tools | | propose | writes to a real database on your disk | | recall | searches that database and returns ranked entries | | get_context | a digest of what you confirmed most recently | | manage | read one entry, list what is pending, forget, restore | | say / board | a shared message board for coordinating several agents |

Storage is SQLite at ~/.memory-hive/hive.db by default. Search is lexical — character bigrams for Chinese, words for Latin script — so it ranks well when the words overlap and finds nothing when they do not. There are no embeddings and no vector index. Every response says "mode": "local" so you can always tell which engine answered.

Excerpt — the full document is on GitHub.

Alternatives to Memory Hive

Maintain Memory Hive? Add a badge to your README

Shows its health grade, and links readers to install steps for every client.

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Catalog data refreshed Oct 27, 2026. Something wrong? Report it.