Your memory logic Executed by xmemory

Define extraction, storage, and update behaviour in schemas written by developers or agents. xmemory executes that specification through MCP, CLI, APIs, and integrations. Test and evolve your memory logic alongside your workflow code.

Diagram showing agents using a natural language read and write interface through MCP, API, CLI, and libraries into the xmemory engine and schema-grounded memory

Control without the maintenance burden

Your schemas are the programming language for memory. Developers and agents define the rules, test their behaviour, and evolve them with the application. xmemory runs the extraction and storage pipeline according to that specification.

01

Schema defines the boundary

Choose which objects, fields, and relations can be stored. Their descriptions do more than supply product terminology: they fine-tune detection, disambiguation, classification, relations, normalization, and grounded derivation of schema-valid facts.

02

Structured and natural-language APIs

Write from messy context, explicit fields, or both. Scope reads and writes when your product knows the shape, while keeping flexible memory for everything less structured.

03

Freshness and conflict policy

Configure what counts as non-conflicting state, how facts should update, and when memories expire with TTL, so stale or contradictory memory does not become manual maintenance.

04

Import, export, and leave cleanly

Bring existing memory into xmemory, inspect what is stored, and export it when needed. Your memory stays a product asset, not a vendor trap.

Focused memory starts with schema

xmemory is a memory engine for saving and retrieving the facts that matter to your workflow. We do not believe useful memory means saving everything. We believe memory should be focused on your product, vertical, and agent task.

Not a transcript dump

Agents see too much context to remember all of it. xmemory is for the durable facts your product needs later, not every intermediate message.

Schema defines focus

Schema is a programming language for memory. It tells the engine which objects, facts, and relationships matter for your workflow.

Vertical by design

Support, sales, coding, research, and operations need different memory. Schema makes that domain model explicit instead of hidden in prompts.

The memory harness xmemory covers

xmemory executes the memory specification you maintain. The engine applies your extraction instructions, maps facts to your schema, validates records, and manages memory operations while your product logic stays explicit and testable.

01

Data extraction & Schema mapping

Turn natural-language writes into facts that match your memory model.

02

Validation & Type enforcement

Keep stored memory aligned with expected fields, types, and constraints.

03

Deduplication & Stateful updates

Update the current state instead of accumulating conflicting notes.

04

Relations & Queryable state

Store facts as connected state that can answer direct product questions.

05

Provenance & Observability

See where memory came from and how reads and writes changed it.

06

Governance

Control access, review sensitive memory, and keep humans in the loop.

07

Schema creation & Evolution

Author or generate schemas, test changes, and review migrations as your workflow evolves.

08

Async write queue

Let agents keep moving while memory writes are processed reliably.

Agent-native connectivity and integrations

Connect xmemory where your agents already work: through MCP tools, CLI flows, direct APIs, language SDKs, or pre-built integrations for common agent frameworks and automation stacks.

Console to see inside memory

xmemory Console home dashboard with operation charts, instance table, and API controlsxmemory Console inspect view showing filtered memory operationsxmemory Console operation detail showing extracted objects, relations, and input text

Operation history

See and query every memory operation for testing, debugging, and incident resolution.

Table view

Open the current data in tables for full transparency on what AI knows now.

Manual control

Edit data manually when you need explicit control over the truth and policies agents rely on.

Access control

Control API keys and permissions to protect data from unauthorised agentic corruption.