210+
REST API Endpoints
29
MCP Tools
10
Entity Types
6
Background Agents
Built for How AI Actually Works
Six infrastructure solutions that give AI systems the memory layer they've been missing.
The Problem:
AI agents lose all context between sessions. Every conversation starts from zero. Custom memory solutions are fragile, unstructured key-value stores that don't scale.
The Solution:
ACE3 provides a typed, structured memory layer accessible via Python SDK, REST API, or MCP protocol. Store 10 entity types with relationships, search semantically, and let background agents maintain data quality automatically.
Integration Methods:
- Python SDK —
pip install ace3-memorywith async/sync clients and Pydantic models - MCP Protocol — 29 tools, 9 resources, 6 prompts for Claude, Cursor, VS Code, ChatGPT, Gemini
- REST API — 210+ endpoints accessible from any language or framework
Any AI agent gets persistent memory in 3 lines of code.
The Problem:
AI coding assistants forget everything when sessions end. Architecture decisions, debugging context, project conventions — all lost. You repeat yourself constantly across tools.
The Solution:
ACE3 connects to every major AI coding tool via MCP. Decisions, patterns, issues, and architecture are stored once and available everywhere. Switch between Claude Code, Cursor, and ChatGPT with the same memory.
Supported Tools:
- Claude Desktop & Claude Code
- Cursor & VS Code (Continue)
- ChatGPT (Codex CLI & Custom GPTs)
- Gemini & any REST-capable tool
- Windsurf & GitHub Copilot
One memory store, every AI tool. No vendor lock-in.
The Problem:
Project knowledge exists as isolated fragments. Decisions aren't linked to the issues they resolve. Architecture components aren't connected to the patterns they implement. Context is flat and disconnected.
The Solution:
ACE3's knowledge graph connects all 10 entity types with 12 semantic relationship types. Traverse connections up to 4 levels deep, query point-in-time snapshots, and visualize the entire project structure interactively.
Capabilities:
- 12 relationship types (implements, resolves, depends_on...)
- Temporal queries — see the graph at any point in time
- Hybrid search — semantic + keyword + graph-aware
- Auto-generated by AI Builder from project descriptions
Knowledge that's connected, not just stored.
The Problem:
Turning requirements into actionable plans takes hours. Writing decisions, decomposing architecture, creating issues, linking dependencies — tedious manual work before any code is written.
The Solution:
Describe what you want to build in natural language. AI Builder generates a complete project plan — issues, decisions, architecture components, best practices, patterns — all linked together in the knowledge graph. One API call.
What Gets Created:
- Issues with priorities, descriptions, and dependencies
- Architecture decisions with rationale and alternatives
- System components with technology stack mapping
- Best practices and coding patterns for the project
- 50-100+ entities with knowledge graph relationships
Hours of planning work done in seconds. Atomically.
The Problem:
Memory systems degrade over time. Stale data accumulates, duplicates multiply, search quality drops, and relationships become inconsistent. Manual maintenance doesn't scale.
The Solution:
Six autonomous background agents run on configurable intervals to maintain your memory infrastructure. They handle cleanup, consolidation, triage, graph maintenance, context optimization, and pattern learning — no intervention required.
6 Background Agents:
Cleanup
Remove stale data
Consolidator
Merge duplicates
Triage
Categorize & prioritize
Graph Maintenance
Validate relationships
Context Optimizer
Optimize search
Learning Agent
Extract patterns
Memory that gets better over time, automatically.
The Problem:
Team knowledge lives in individual heads and scattered tools. New members take weeks to onboard. Decisions get relitigated because nobody remembers the rationale. Vendor-hosted memory means giving up control of your data.
The Solution:
ACE3 runs on your own PostgreSQL database. Namespaces isolate projects, role-based access controls who sees what, and every team member's AI tools share the same knowledge. Your data never leaves your infrastructure.
Enterprise Features:
- Customer-hosted PostgreSQL — zero marginal storage cost
- Multi-member organizations with namespace isolation
- Full data privacy — memory stays on your infrastructure
- SSO, audit logs, and SOC2 compliance (coming)
Infrastructure you own. Knowledge that compounds.
How It Fits Together
ACE3 sits between your AI tools and your database
Your AI Tools
ACE3 Memory Infrastructure
Your Database
Customer-Hosted PostgreSQLThe ACE3 Difference
First-generation memory stores vs. second-generation memory infrastructure
- Start every AI conversation from scratch
- Unstructured key-value blobs
- No relationships between memories
- Memory degrades over time
- Locked to one AI platform
- Vendor hosts your data
- Perfect context in every session, any tool
- 10 typed entities with full CRUD
- Knowledge graph with 12 relationship types
- 6 background agents maintain quality
- Works with every AI via MCP, REST, SDK
- Runs on your own PostgreSQL