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  1. Home
  2. ๐Ÿง  Knowledge & Memory
  3. Zaxy
Zaxy logo
Health: ActiveRecent health check succeeded.Last checked 9/11/2026, 7:47:05 PM

Zaxy

User RatingsBe the first to rate and review this MCP server!
View Repository17 GitHub StarsTotal stargazers on GitHub for the source repository (17 stars).Visit Website

Event-sourced append-only log memory with embedded temporal knowledge graph for auditable agent context and team coordination.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag โ€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON โ–พ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "syndicalt-zaxy": {
      "command": "uvx",
      "args": [
        "zaxy-memory"
      ]
    }
  }
}

๐Ÿ’ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives๐Ÿง  More in Knowledge & Memory

Overview

This server provides a durable, auditable memory system for AI agents using an append-only JSONL event log combined with an embedded temporal knowledge graph (LadybugDB). It supports capturing detailed agent context including missions, sessions, observations, and citations, enabling query, replay, and inspection of project history. The design isolates parent and worker sessions until review and merge, facilitating agent-team coordination. It runs locally by default without requiring sidecars and integrates with multiple MCP clients.

Use cases

โ€ขCapture and audit agent session histories and observations
โ€ขCoordinate multi-agent workflows with isolated session merging
โ€ขQuery and replay event-sourced project memory for reasoning
โ€ขManage memory with salience-based forgetting and token-budgeted checkout
โ€ขIntegrate memory into MCP clients like Codex, Claude Code, and Hermes Agent

Key features

โ€ขAppend-only JSONL event log as source of truth
โ€ขEmbedded LadybugDB temporal knowledge graph projection
โ€ขSalience-based memory attenuation instead of deletion
โ€ขToken-budgeted memory checkout and review-gated consolidation
โ€ขLocal-first runtime with optional Neo4j or Pathlight sidecars
โ€ขMCP-native interface with 47 tools and an 8-tool core profile

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Zaxy.

Extracted Tool Capabilities
Append-only JSONL event log as source of truth
Embedded LadybugDB temporal knowledge graph projection
Salience-based memory attenuation instead of deletion
Token-budgeted memory checkout and review-gated consolidation
Local-first runtime with optional Neo4j or Pathlight sidecars
MCP-native interface with 47 tools and an 8-tool core profile

Documentation Overview

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 LadybugDB 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 LadybugDB graph projection is the default local runtime.

The plain install uses embedded LadybugDB. 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 LadybugDB, no Neo4j sidecar.
  • MCP-native integration: Codex, Claude Code, Cursor, VS Code, Hermes Agent, LangGraph, CrewAI, and AutoGen can use the same memory interface.

Benchmark claims withdrawn (2026-07-03). The prior LongMemEval numbers were withdrawn: they were produced in oracle mode (mean ~1.9 candidate sessions per question, so Recall@5/citation-coverage were ~1.0 by construction, not by retrieval) and the preference-question scores rested on a hardcoded answer table that has since been removed. Zaxy does not currently publish a LongMemEval score. A real, full-haystack LongMemEval run is planned; until it lands, treat the earlier 0.956/0.910/1.000 figures as retracted. The Harvey LAB claim is pending the same audit.

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 <task> 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.

Architecture

Code
Agent (LangGraph / Any MCP Client)
    |
    v
MCP Server โ€” memory_append / memory_query / memory_feedback / memory_replay / memory_invalidate
    |
    v
Eventloom (immutable JSONL log)  โ†’  Hybrid Extraction  โ†’  Embedded LadybugDB graph
    |                                                               |
    +โ€”โ€”โ€”โ€”โ€”โ€” Optional Pathlight traces โ€”โ€”โ€”โ€”โ€”โ€”โ€”โ€”โ€”โ€”โ€”โ€”โ€”โ€”โ€”โ†’  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.

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
  • Memory export contract: docs/export-contract.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 (60โ€“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

FilePurpose
src/zaxy/event.pyEventloom JSONL I/O + hash chain integrity
src/zaxy/extract.pyHybrid extraction engine + rule registry
src/zaxy/embedded_graph_store.pyEmbedded LadybugDB projection store
src/zaxy/graph.pyOptional Neo4j bi-temporal wrapper via zaxy-memory[neo4j]
src/zaxy/query.pyHybrid retrieval router
src/zaxy/mcp_server.pyMCP stdio/SSE server
src/zaxy/trace.pyOptional Pathlight observability hooks
src/zaxy/core.pyMemoryFabric orchestrator
src/zaxy/session.pyPer-session Eventloom log manager
src/zaxy/security.pyShared validation and input bounds
src/zaxy/__main__.pyCLI (zaxy serve, zaxy replay, etc.)

Production Secrets

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

VariableSecret-file variant
NEO4J_PASSWORDNEO4J_PASSWORD_FILE
MCP_ADMIN_TOKENMCP_ADMIN_TOKEN_FILE
PATHLIGHT_ACCESS_TOKENPATHLIGHT_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: โ‰ฅ92% 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

Read the full README โ†’View source on GitHub โ†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks โ€” not a rating.

GitHub stars
17
Stargazers on the source repository.
Last commit
1mo ago
Most recent push to the default branch.
Directory activity
1 views
Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet โ€” be the first to share how this listing worked for you.

Frequently Asked Questions about Zaxy

No, Zaxy uses an embedded LadybugDB graph projection by default and does not require a Neo4j sidecar unless explicitly installed.

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Technical Specs & Signals

Category๐Ÿง Knowledge & Memory
More technical detailsExpand โ–พ
TransportSTDIO
RuntimePython
Last updatedAug 10, 2026
10/11 checks healthy over the last 33d
Views1
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars17
GitHub Star CountTotal stargazers on GitHub representing community popularity (17 stars).
Last commit1mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Aug 10, 2026
52Quality signal: Good ยท 52/100How this signal is calculated โ–พ
Server availabilityNot measured

Not scored for repo-hosted servers โ€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools24/30
Adoption & activity5/15
Community engagement0/10

A guidance signal from public completeness & health data โ€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

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Scanned 15d ago via OSV.dev ยท zaxy-memory (PyPI)

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