Eidet

eidet-sdk

Python client SDK for Eidet — long-term memory for AI coding agents.

Install

pip install eidet-sdk

Usage

from eidet_sdk import EidetClient, MemoryType

client = EidetClient()  # defaults to http://localhost:19380

# Store a memory
result = client.store(
    repo="/path/to/project",
    content="The auth module uses JWT with RS256 signing",
    type=MemoryType.OBSERVATION,
    tags=["auth", "jwt"],
)

# Search memories
results = client.recall("/path/to/project", "authentication")

# Get session context (L0 identity + L1 top memories, < 600 tokens)
context = client.context("/path/to/project")

# Browse all memories
page = client.browse("/path/to/project", skip=0, take=50)

# Feedback loop
client.feedback("memories/...", was_used=True)   # echo (useful)
client.feedback("memories/...", was_used=False)  # fizzle (irrelevant)

Context Manager

with EidetClient(url="http://localhost:19380") as client:
    results = client.recall("/path/to/project", "deployment")

API Key Authentication

client = EidetClient(url="http://localhost:19380", api_key="your-api-key")

All Methods

Method Description
store(repo, content, ...) Store a memory (observation, insight, procedure, heuristic; negative/valence for dead-ends, stage for subtask scoping)
recall(repo, query, **kwargs) Search memories by meaning and keywords (filters: type, tags, valence, stage, cross_repo)
context(repo) Get compact session context (< 600 tokens)
get_memory(id) Get a specific memory by ID (includes contentSha256 for optimistic concurrency)
update(memory_id, **kwargs) Update a memory (content changes create versions; expected_content_sha256 precondition)
redact(memory_id, reason) Scrub a memory's content to a tombstone
forget(id, reason?) Soft-delete a memory
feedback(memory_id, was_used) Echo (useful) or fizzle (irrelevant) feedback
history(id) Get version chain for a memory
browse(repo, **kwargs) Paginated memory listing
graph(repo, limit?) Graph data for visualization
repos() List all known repositories
intake(repo) Ingest project files as seed memories
intake_git(repo, **kwargs) Seed memories from git commit history
intake_claude_memory(repo, dry_run?) Import Claude Code's native per-project memory
consolidate(repo) Merge related observations into insights
maintenance(repo) Run maintenance pipeline
export_markdown(repo, format?) Export memories as markdown ("agents" for AGENTS.md shape)
health() Health check
status() Service status and stats
is_available() Check if the service is reachable

Requirements

  • Eidet service running locally (eidet serve or installed as system service)
  • Python 3.10+
  • httpx

License

MIT

Project links

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Latest release

1 maintainer

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Avatar for stevehansen from gravatar.com stevehansen

GitHub Statistics

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License

MIT

Requires

Python >=3.10

Tags

eidet memory ai coding-agent mcp

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