Skip to main content

Personal conversation knowledge base — import, search, and analyze conversations from ChatGPT, Claude, Gemini, and Claude Code

Project description

memex

Personal conversation knowledge base. MCP-first architecture for managing, searching, and analyzing chat conversations from multiple AI providers.

Install

pip install -e ".[dev]"

Quick Start

Import conversations:

memex import conversations.json          # auto-detects format
memex import export.json --format openai  # force format

Export:

memex export output.md --format markdown
memex export output.json --format json

Browse and search:

memex show                               # list conversations
memex show <id>                          # view a conversation

HTML export (self-contained SPA):

memex export ./site --format html        # outputs index.html + DB + assets

MCP server (for Claude Desktop, etc.):

memex mcp

Scripts:

memex run --list                         # available scripts
memex run redact --words "secret" --level word --apply
memex run enrich_trivial --apply

Supported Formats

Format Import Export
OpenAI Yes -
Anthropic Yes -
Gemini Yes -
Claude Code Yes -
Markdown - Yes
JSON - Yes
HTML (SPA) - Yes

MCP Tools

When running as an MCP server, memex exposes 4 tools:

  • execute_sql -- Primary read interface: all queries via SQL (read-only by default)
  • get_conversation -- Tree-aware retrieval + export (metadata, messages, markdown/JSON)
  • update_conversations -- Modify properties, tags, and enrichments (bulk)
  • append_message -- Add messages to conversation trees

Development

pytest tests/memex/ -v             # run tests
pytest tests/memex/ --cov=memex    # with coverage

License

MIT

Project details


Download files

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

Source Distribution

py_memex-0.10.0.tar.gz (62.3 kB view details)

Uploaded Source

Built Distribution

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

py_memex-0.10.0-py3-none-any.whl (71.6 kB view details)

Uploaded Python 3

File details

Details for the file py_memex-0.10.0.tar.gz.

File metadata

  • Download URL: py_memex-0.10.0.tar.gz
  • Upload date:
  • Size: 62.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.3

File hashes

Hashes for py_memex-0.10.0.tar.gz
Algorithm Hash digest
SHA256 18401f8435a40456c65b53fd510fa2bed860bf38a28c96287ebd9e876d9836cd
MD5 6d143b88dabec3a8c16f0b9565b1d9a8
BLAKE2b-256 254dc17eb268a47d068d1878c1699c8cc24ae68b7879aa003ab392ecb56bcbda

See more details on using hashes here.

File details

Details for the file py_memex-0.10.0-py3-none-any.whl.

File metadata

  • Download URL: py_memex-0.10.0-py3-none-any.whl
  • Upload date:
  • Size: 71.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.3

File hashes

Hashes for py_memex-0.10.0-py3-none-any.whl
Algorithm Hash digest
SHA256 351d0d3d01c4f5206409ab547f45b4175fec18c785369a459781167579ecebeb
MD5 5416a5635e4a3988052fce8249c9ac02
BLAKE2b-256 7ae9e621b9509909529e46f2985cf640894f329d860ce496188ec785bb5849f9

See more details on using hashes here.

Supported by

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