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https://github.com/syndicalt/zaxy

Zaxy turns agent work into durable memory: an Eventloom log for audit, hash-linked provenance for replay, a Neo4j temporal graph for reasoning, Memory Checkout for compact context, and MCP tools for model-facing retrieval, capture, and feedback.
https://github.com/syndicalt/zaxy

ai ai-agents ai-memory llm-tools

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Zaxy turns agent work into durable memory: an Eventloom log for audit, hash-linked provenance for replay, a Neo4j temporal graph for reasoning, Memory Checkout for compact context, and MCP tools for model-facing retrieval, capture, and feedback.

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# Zaxy



**Production memory for agent teams that need receipts.**



Zaxy turns agent context into an auditable project memory fabric. It captures

parent missions, worker sessions, tool observations, cited findings, conflict

review, approval packets, and accepted merge-back into one durable history that

can be queried, replayed, and inspected.



Under the hood, Zaxy uses Eventloom append-only JSONL as the source of truth and

an embedded Kuzu graph projection for local reasoning. It is built for agents

that need to remember what happened, cite where it came from, and avoid turning

project state into a pile of markdown files and vector chunks.



The embedded Kuzu graph projection is the default local runtime.



The plain install uses embedded Kuzu. Install `zaxy-memory[neo4j]` only for the

optional Neo4j sidecar, and `zaxy-memory[pathlight]` only for Pathlight tracing.



## Why It Matters



- **Auditable memory**: every accepted fact can point back to Eventloom history.

- **Agent-team coordination**: parent and worker sessions stay isolated until

  findings are reviewed and merged.

- **Local-first runtime**: the default path uses embedded Kuzu, no Neo4j sidecar.

- **MCP-native integration**: Codex, Claude Code, Cursor, VS Code, Hermes Agent,

  LangGraph, CrewAI, and AutoGen can use the same memory interface.

- **External benchmark evidence**: on the full Harvey LAB legal-agent memory

  benchmark, Zaxy scored `0.788` mean criterion pass rate across `10/10` tasks,

  `+0.184` vs regular/no-memory, `+0.081` vs the article-best task rows, and

  won `9/10` task comparisons. See

  [Benchmarks](docs/benchmarks.md#harvey-lab); the published

  stats artifact is `reports/benchmarks/harvey-lab-memory-ablation/publishable-statistics.md`.

- **Headline 500 evidence**: the current LongMemEval-compatible checkout

  diagnostic is a full 500-question run with mean `0.956`, Answer@5 `0.910`,

  Recall@5 `1.000`, and citation coverage `1.000`. See

  [Benchmarks](docs/benchmarks.md#headline-500).



## Quick Start



### Install, init, verify



```bash

pipx install zaxy-memory

zaxy init

zaxy memory log --eventloom-path .eventloom --limit 5

zaxy memory bootstrap --eventloom-path .eventloom

zaxy doctor --eventloom-path .eventloom

```



The PyPI distribution is `zaxy-memory`; the import package and console command

are still `zaxy`. Bare `zaxy init` sets up the local embedded graph posture,

repo-local profile, deterministic capture config, genesis event, heartbeat, and

MCP guidance. For Codex, the printed activation launcher starts the managed

capture watcher when the local capture config is present; pass `--capture start`

only when you want init itself to start the watcher before opening Codex. The

default human output is compact and action-first; add `--verbose` when you need

the full setup diagnostics, optional checks, fallback commands, resume guidance,

and notes.

For automation, `zaxy init --json` keeps the raw onboarding fields and adds

`setup.status`, `setup.issues`, `setup.pending`, `readiness.status`,

`readiness.reasons`, `readiness.actions`, and structured

`readiness.action_items` for both commands and non-command review tasks. Each

structured action carries `label`, `command`, original `source`, and `hints`

for compact-output tips such as activation `` replacement and path-stable

command guidance. Installers can render those tips without parsing prose. It also

includes `setup.summary`, `readiness.summary`,

`readiness.required_action_count`, and `readiness.reason_count`, so client UIs

can render compact status without parsing human output. It also

separates `readiness.blocking_diagnostics` from

`readiness.non_blocking_diagnostics` so scripts can distinguish setup

completion, required actions, and advisory doctor warnings before relying on

live memory.



For Codex, `zaxy init --codex-mcp-install auto` is the default. It writes or

reuses the user-level Codex MCP config when that can be done without replacing

an existing `zaxy` server entry. If no safe config target exists, it prints the

copyable `codex mcp add` command. If an existing `zaxy` entry differs, it asks

you to review that config before replacing it because Codex can silently replace

servers with the same name. Use an explicit mode when you need to force one side

of that decision after review:



```bash

zaxy init --codex-mcp-install user

# or: zaxy init --codex-mcp-install command

```



Both Codex paths keep the server workspace-neutral. After init, start or

restart Codex through the printed `zaxy activate codex ... --launch` command so

the MCP server list and Zaxy activation packet are loaded together. The printed

command includes explicit `--eventloom-path` and `--workspace-root` values, so

it still targets the initialized repo when copied from another shell.



Run the single-agent memory example:



```bash

python examples/single_agent_memory.py

```



Your local data lives under `.eventloom/` as one append-only JSONL file per

session.



For Claude Code instead of Codex:



```bash

zaxy init . --domain my-project --preset local-claude --infra check

```



For Hermes Agent:



```bash

zaxy ide-config hermes --install

```



For repository development, use `pip install -e ".[dev]"`, `./scripts/setup.sh`,

and `zaxy status`. Start Docker sidecars only for integration tests or explicit

backend comparisons. Production setup writes Docker secret files under

`./secrets/`; see [docs/deployment.md](docs/deployment.md).



## Architecture



```

Agent (LangGraph / Any MCP Client)

    |

    v

MCP Server — memory_append / memory_query / memory_feedback / memory_replay / memory_invalidate

    |

    v

Eventloom (immutable JSONL log)  →  Hybrid Extraction  →  Embedded Kuzu graph

    |                                                               |

    +—————— Optional Pathlight traces ———————————————→  Query Router

                                                              |

                                                    Hybrid Retrieval

                                                    (exact + BM25 + vector + traversal)

```



Zaxy also includes an observe-only OpenAI-compatible packet analyzer for model

call provenance. It forwards packets to one configured upstream endpoint and

records `llm.packet.completed` events to Eventloom without acting as a router.

See [LLM Packet Analyzer](docs/packet-analyzer.md).



## Public Site and Documentation



- Public static site: `site/index.html`

- Why Zaxy: `docs/why-zaxy.md`

- Getting started: `docs/getting-started.md`

- MCP quickstart: `docs/mcp-quickstart.md`

- Architecture: `docs/architecture.md`

- Configuration: `docs/configuration.md`

- MCP interface: `docs/mcp.md`

- Eventloom contract: `docs/eventloom.md`

- Graph schema: `docs/graph-schema.md`

- Retrieval: `docs/retrieval.md`

- Benchmarks: `docs/benchmarks.md`

- LLM packet analyzer: `docs/packet-analyzer.md`

- Embeddings: `docs/embeddings.md`

- Security: `docs/security.md`

- Operations and deployment: `docs/operations.md`, `docs/deployment.md`, `docs/runbook.md`

- Python API: `docs/api.md`

- Stability commitment: `docs/stability-commitment.md`

- Migration guide: `docs/migration.md`

- Archived benchmark iteration notes, release drafts, and research notes live

  under `docs/archive/`, `docs/announcements/`, and `docs/research/`.

- Contributing: `CONTRIBUTING.md`



## Key Features



- **Immutable audit trail**: Eventloom append-only JSONL with SHA-256 hash chains.

- **Bi-temporal graph**: Facts have validity windows (`valid_from`, `valid_to`).

- **Hybrid extraction**: Rule-based for typed events (60–80% cost reduction), LLM fallback.

- **Hybrid retrieval**: Exact + keyword + vector + graph traversal with configurable fusion weights.

- **Session sharding**: One Eventloom log per agent/session, with a shared graph.

- **MCP-native**: Drop-in memory for any MCP-compatible agent framework over stdio or SSE.

- **Observable**: Optional Pathlight traces, breakpoints, and diff support via `zaxy-memory[pathlight]`.

- **Hardened local defaults**: bounded MCP inputs, safe session IDs, no-sidecar embedded graph projection, and optional admin token support for replay/invalidation.



## Project Structure



| File | Purpose |

|------|---------|

| `src/zaxy/event.py` | Eventloom JSONL I/O + hash chain integrity |

| `src/zaxy/extract.py` | Hybrid extraction engine + rule registry |

| `src/zaxy/embedded_graph_store.py` | Embedded Kuzu projection store |

| `src/zaxy/graph.py` | Optional Neo4j bi-temporal wrapper via `zaxy-memory[neo4j]` |

| `src/zaxy/query.py` | Hybrid retrieval router |

| `src/zaxy/mcp_server.py` | MCP stdio/SSE server |

| `src/zaxy/trace.py` | Optional Pathlight observability hooks |

| `src/zaxy/core.py` | MemoryFabric orchestrator |

| `src/zaxy/session.py` | Per-session Eventloom log manager |

| `src/zaxy/security.py` | Shared validation and input bounds |

| `src/zaxy/__main__.py` | CLI (`zaxy serve`, `zaxy replay`, etc.) |



## Production Secrets



Zaxy supports Docker/Kubernetes-style secret files for sensitive settings:



| Variable | Secret-file variant |

|----------|---------------------|

| `NEO4J_PASSWORD` | `NEO4J_PASSWORD_FILE` |

| `MCP_ADMIN_TOKEN` | `MCP_ADMIN_TOKEN_FILE` |

| `PATHLIGHT_ACCESS_TOKEN` | `PATHLIGHT_ACCESS_TOKEN_FILE` |



Direct environment variables take precedence over their `*_FILE` variants.

Use `docker-compose.prod.yml` as the production compose baseline.



## Development



- **Tests first** (Karpathy rule). Every public function has a test.

- **Unit tests** mock external services. **Integration tests** use Docker for optional sidecar backends.

- **Coverage gate: ≥92%** enforced by CI.

- **Lint/format**: `ruff`. **Types**: `mypy`.



```bash

# Run full suite with coverage gate

pytest



# Run integration tests (requires Docker)

./scripts/generate-certs.sh .certs

docker compose --profile integration up -d neo4j-test neo4j-tls

pytest -m integration --no-cov



# Lint and type-check

ruff check src tests

mypy src



# Current full-set LongMemEval-compatible checkout evidence:

# reports/benchmarks/longmemeval-500-publish-20260607/

# Mean 0.956, Answer@5 0.910, citation coverage 1.000, R@1/R@5/R@10 0.960/1.000/1.000.



# Stage the next full 500 only after docs/report cleanup is complete.

zaxy benchmark --output-dir reports/benchmarks/longmemeval-500-next \

  --embedding-provider hash --workload longmemeval \

  --dataset .cache/zaxy/benchmarks/longmemeval_oracle.json \

  --runs 1 --limit 5 --baseline-backends bm25 \

  --projection-backend embedded --zaxy-backend checkout



# Harvey LAB external memory-ablation comparison

# Consumes externally generated Harvey normalized-result artifacts for Zaxy;

# does not reuse LongMemEval statistics as legal-agent benchmark evidence.

# Current full external Harvey LAB evidence:

# reports/benchmarks/harvey-lab-memory-ablation/publishable-statistics.md

# reports/benchmarks/harvey-lab-memory-ablation/harvey-lab-benchmark.json

# 10/10 tasks, mean criterion pass rate 0.788, +0.184 vs regular/no-memory,

# +0.081 vs article-best task rows, 9/10 wins vs article-best rows.



# Production deployment preflight

scripts/validate-deployment.sh --root .



# Build and validate Python release artifacts

scripts/build-dist.sh --root .



# Verify local release metadata, PyPI Trusted Publishing, and LangGraph smoke

zaxy doctor --release-smoke



# Validate public site and documentation links

scripts/validate-docs.sh --root .



# Clean-repo beta UAT: install into a throwaway workspace and verify init,

# bootstrap, deterministic capture, doctor, and memory checkout.

scripts/beta-uat.sh



# Summarize beta readiness gates without external services.

zaxy doctor --beta-readiness



# Go-live release gate

scripts/release-check.sh --root .

```



The full suite must stay at or above 92% coverage before a sprint is complete.



## Release Publishing



The PyPI distribution name is `zaxy-memory` because `zaxy` is already occupied

on PyPI. Published releases build from GitHub Actions and upload to

 using PyPI Trusted Publishing with

GitHub OIDC. The import package and console command remain `zaxy`.



Before publishing, run `zaxy doctor --release-smoke` to verify the package

version, changelog entry, release workflow, tokenless publishing posture, and

dependency-light LangGraph example.



## License



MIT