Skip to main content

heropen

Give your AI agent long-term memory. Data stays on your machine; search costs zero tokens.

Why "heropen"

The name comes from two places: her from Hermes (the agent you are reading this with), open from OpenClaw (openness). her + open put together is heropen.

Written out, heropen starts with hero — evoking the Marvel superhero trope. It is a memory layer that remembers you and writes things down for your agent.

Install

pip install heropen

Restart your agent. That's it.

On first launch it auto-detects your agent (Claude Code, Cursor, Windsurf, or any MCP client), sets up the database, and registers the memory tools. Your agent will notice the new install and walk you through setup.

30-second quickstart

# Save a memory
heropen add "Project uses FastAPI + SQLAlchemy, tests with pytest"

# Search memories
heropen search "project tech stack"

# Check status
heropen status

# Diagnose issues
heropen diagnose

Connect your agent (MCP)

Works with any MCP-compatible agent. v1.8+ auto-detects and configures — no manual steps.

Or add it manually to your agent config:

{
  "mcpServers": {
    "heropen": {
      "command": "heropen",
      "args": ["mcp"]
    }
  }
}

Restart your agent and it has memory. Store a bug fix once, remember it permanently across sessions.

Privacy promise

Data stays on your machine. No telemetry. No heartbeat pings. All memory is stored in a local SQLite database. Vector search uses a local embedding model by default (fastembed, pip install heropen[embedding]) — fully offline, zero cost. Optionally, you can point it at your own self-hosted embedding endpoint by setting the EMBEDDING_ENDPOINT and EMBEDDING_API_KEY environment variables (OpenAI-compatible /v1/embeddings), so no third-party cloud is ever billed. Memory text is only used to generate vectors and is never reported.

If neither a local embedding model nor a self-hosted endpoint is configured, search automatically degrades to fast full-text (FTS) matching — still fully offline and zero cost. So pip install heropen works with zero setup; embeddings only upgrade search quality, they never gate basic use.

Open-source scope

The free edition is fully open source (Apache-2.0). The commercial layer (Plus / Enterprise) is closed source.

Why heropen

heropen (free) other solutions
Storage unlimited usually capped
Searches unlimited pay per query
Needs network no yes
Data ownership your machine their servers
Install one pip install server + config

Free = full core features. No crippled functionality.

Links

License

Apache-2.0

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

heropen-1.8.9.tar.gz (211.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

heropen-1.8.9-py3-none-any.whl (83.6 kB view details)

Uploaded Python 3

File details

Details for the file heropen-1.8.9.tar.gz.

File metadata

  • Download URL: heropen-1.8.9.tar.gz
  • Upload date:
  • Size: 211.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.14

File hashes

Hashes for heropen-1.8.9.tar.gz
Algorithm Hash digest
SHA256 1d9b57d09f5bea7d0072d8896699f4255e74e2d914c7accc62730b9e8178d325
MD5 84871f0e4c544bca9635f92dbb9bdbdf
BLAKE2b-256 f3e0e3fe30eab96b721f97847a9625323156ac9b6163f68675562b60071506f3

See more details on using hashes here.

File details

Details for the file heropen-1.8.9-py3-none-any.whl.

File metadata

  • Download URL: heropen-1.8.9-py3-none-any.whl
  • Upload date:
  • Size: 83.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.14

File hashes

Hashes for heropen-1.8.9-py3-none-any.whl
Algorithm Hash digest
SHA256 765acb8eb093edacefcb33e483cf2d47fdf757f8d2ec679c2fc2d466e22e7547
MD5 21b963dc8d446ec9b6ecd1c5af34171f
BLAKE2b-256 9743580335f3a8af4861f420ea7e076fa244eb4d7bdac7c899eaef8e0143e5b5

See more details on using hashes here.

Release history Release notifications | RSS feed

1.9.1

2 files

1.9.0

2 files

This release

1.8.9 This release

2 files

1.8.8

2 files

1.8.7

2 files

1.8.6

2 files

1.8.5

2 files

1.8.4

2 files

1.8.3

2 files

1.8.2

2 files

1.8.1

2 files

1.8.0

2 files

1.7.32

2 files

1.7.31

2 files

1.7.30

2 files

1.7.29

2 files

1.7.28

2 files

1.7.27

2 files

1.7.26

2 files

1.7.25

2 files

1.7.24

2 files

1.7.23

2 files

1.7.22

2 files

1.7.21

1 file

1.7.20

1 file

1.7.19

1 file

1.7.18

1 file

1.7.17

1 file

1.7.16

1 file

1.7.15

1 file

1.7.14

1 file

1.7.13

1 file

1.7.12

1 file

1.7.11

1 file

1.7.10

1 file

1.7.9

1 file

1.7.8

1 file

1.7.7

1 file

1.7.6

1 file

1.7.5

1 file

1.7.4

1 file

1.7.3

1 file

1.7.2

2 files

1.7.1

2 files

1.7.0

2 files

1.6.3

1 file

1.6.2

1 file

1.6.1

1 file

1.6.0

1 file

1.5.4

1 file

1.5.3

2 files

1.5.2

2 files

1.5.1

2 files

1.5.0

2 files

1.4.9

2 files

1.4.8

2 files

1.4.7

2 files

1.4.6

2 files

1.4.5

2 files

1.4.4

2 files

1.4.3

1 file

1.4.2

1 file

1.4.1

1 file

1.4.0

1 file

1.3.1

2 files

1.3.0

2 files

1.2.0

1 file

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page