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 also a companion that remembers you and writes things down for you.

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-1.8.7.tar.gz (206.5 kB view details)

Uploaded Source

Built Distribution

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

heropen-1.8.7-py3-none-any.whl (77.8 kB view details)

Uploaded Python 3

File details

Details for the file heropen-1.8.7.tar.gz.

File metadata

  • Download URL: heropen-1.8.7.tar.gz
  • Upload date:
  • Size: 206.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.14

File hashes

Hashes for heropen-1.8.7.tar.gz
Algorithm Hash digest
SHA256 88f36ccb34f4ff27d8bc697f18f4d1240349d18b343d91165ce1f6a20459b2f3
MD5 8dc46295c3a0d75a92103814c525ea1a
BLAKE2b-256 e33efe71d51f07b97f1a4947ba56f592cde425bad5e865c6cf2d17257c1c103b

See more details on using hashes here.

File details

Details for the file heropen-1.8.7-py3-none-any.whl.

File metadata

  • Download URL: heropen-1.8.7-py3-none-any.whl
  • Upload date:
  • Size: 77.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.14

File hashes

Hashes for heropen-1.8.7-py3-none-any.whl
Algorithm Hash digest
SHA256 14ef8ca27d62a32878e388ea6829045d54f79e2a1e6efa78f482d078b796302c
MD5 8ded15f1387caab6107d9f15fae4a72c
BLAKE2b-256 6d145a375489a124375f1600766356f27072b5c6fa3e0ec99587a4a46c743b98

See more details on using hashes here.

Release history Release notifications | RSS feed

1.9.1

2 files

1.9.0

2 files

1.8.9

2 files

1.8.8

2 files

This release

1.8.7 This release

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