# XTrace Memory > Hosted memory for AI agents. Send conversation turns, get back searchable facts. ## Docs - [Archive group](https://docs.xtrace.ai/api-reference/groups/archive-group.md): Soft-delete: flips `status` to `archived`. The group row is retained so memory rows tagged with this id remain searchable; new ingests reject the id with `422 group_archived`. Restore by `PATCH`ing `status` back to `active`. Idempotent. - [Create group](https://docs.xtrace.ai/api-reference/groups/create-group.md): Register a new group on the org. Returns the persisted row including the server-generated `id`. - [Get group](https://docs.xtrace.ai/api-reference/groups/get-group.md) - [List groups](https://docs.xtrace.ai/api-reference/groups/list-groups.md): List groups for the calling org. Active-only by default. - [Update group](https://docs.xtrace.ai/api-reference/groups/update-group.md): Patch `name`, `prompt`, and/or `status`. Changing `prompt` does not retroactively re-tag memory rows that were tagged under the previous prompt. - [Agentic memory search](https://docs.xtrace.ai/api-reference/memories/agentic-memory-search.md): Agentic search over the memory pool. - [Delete memory](https://docs.xtrace.ai/api-reference/memories/delete-memory.md): Hard-delete a memory — fact, artifact, or episode. - [Get memory](https://docs.xtrace.ai/api-reference/memories/get-memory.md): Get one memory by id. Works for facts, artifacts, episodes. Always returns the full representation — artifacts include ``details.full_content``. - [Get revision chain](https://docs.xtrace.ai/api-reference/memories/get-revision-chain.md): Return the revision chain for a memory. - [Ingest memories](https://docs.xtrace.ai/api-reference/memories/ingest-memories.md): Async ingest. Returns ``202 + job_id`` by default; the extraction runs in the background and the caller polls ``GET /v1/memories/jobs/{job_id}``. - [List memories](https://docs.xtrace.ai/api-reference/memories/list-memories.md): List memories with flat-equality filters and cursor pagination. - [Poll ingest job](https://docs.xtrace.ai/api-reference/memories/poll-ingest-job.md): Return the current state of an ingest job. - [Procedural-memory recall (pre-tool-call hook)](https://docs.xtrace.ai/api-reference/memories/procedural-memory-recall-pre-tool-call-hook.md): Procedural-memory recall for a pre-tool-call hook. - [Update memory group_ids](https://docs.xtrace.ai/api-reference/memories/update-memory-group_ids.md): Add or remove ``group_ids`` on a single memory — the sharing axis. Group tags control who can reach a row via ``filters: {group_ids: }`` on search / list, so this is how a memory becomes shared (or un-shared) after ingest. - [Get usage](https://docs.xtrace.ai/api-reference/usage/get-usage.md): Aggregate the org's memory usage for the current quota period — a calendar month, or your billing period on plans that meter per billing period — plus a per-day breakdown if requested, plus an inline storage snapshot. - [Delete webhook config](https://docs.xtrace.ai/api-reference/webhooks/delete-webhook-config.md): Remove the org's webhook config. Idempotent — returns `204` whether or not a config existed. Stops all deliveries for the org. - [Get webhook config](https://docs.xtrace.ai/api-reference/webhooks/get-webhook-config.md): Read the org's current webhook config. The `secret` is masked — the full value is only ever shown at create / rotate time. - [Set webhook config](https://docs.xtrace.ai/api-reference/webhooks/set-webhook-config.md): Create or replace the org's webhook config. Idempotent on `url` / `events` / `enabled`. The full signing `secret` is returned here — on first create, or whenever `rotate_secret=true`. Store it: `GET` only ever returns it masked. - [Authentication](https://docs.xtrace.ai/guides/authentication.md): How API keys and org headers work — and how to wire them into the SDK. - [Groups](https://docs.xtrace.ai/guides/groups.md): Share memory across users. Register a group — prompted or catch-all — tag memories to it at ingest, and let every member search them. - [Ingesting memories](https://docs.xtrace.ai/guides/ingesting-memories.md): Send conversation turns, get back extracted facts. Async by default, with a sync escape hatch. - [Quickstart](https://docs.xtrace.ai/guides/quickstart.md): Install the SDK, ingest a conversation turn, and search it back — in under five minutes. - [Searching memories](https://docs.xtrace.ai/guides/searching-memories.md): Vector search scoped by what you pass — a user's own memories, shared groups, or both. - [TypeScript SDK](https://docs.xtrace.ai/guides/typescript-sdk.md): Reference for the @xtraceai/memory package — every class, method, type, and error. - [Webhooks](https://docs.xtrace.ai/guides/webhooks.md): Get a signed push notification the moment memory learning finishes for a conversation — instead of polling the job endpoint. - [Introduction](https://docs.xtrace.ai/introduction.md): Hosted memory for AI agents. Send conversation turns, get back searchable facts. - [CLI quickstart](https://docs.xtrace.ai/x-vec/cli.md): Set up the xtrace CLI and run the init workflow — create an execution context, configure embeddings, and go from an empty knowledge base to search results in four commands. - [CLI command reference](https://docs.xtrace.ai/x-vec/cli-reference.md): Full usage details for every xtrace CLI command — shared commands, knowledge base admin, and x-vec data commands. - [Configuration](https://docs.xtrace.ai/x-vec/configuration.md): Configure the x-vec SDK via environment variables or constructor parameters — cryptography backends, key providers, DataLoader/Retriever options, and AWS KMS. - [Embedding models](https://docs.xtrace.ai/x-vec/embedding-models.md): Convert text into binary vectors for encrypted storage and search using Ollama, Sentence Transformers, OpenAI, or your own float vectors. - [Installation](https://docs.xtrace.ai/x-vec/installation.md): Install the x-vec Python SDK and optional extras for local embeddings and the CLI. - [XTrace Vector DB — Encrypted vector search](https://docs.xtrace.ai/x-vec/introduction.md): Semantic search with the privacy guarantees of keeping your data on your own machine. Content is AES-encrypted and embedding vectors are homomorphically encrypted before they ever leave your laptop. - [LLM inference](https://docs.xtrace.ai/x-vec/llm-inference.md): Run an LLM over retrieved context for RAG pipelines — with OpenAI, Anthropic, private TEE inference via Redpill, or fully local Ollama. - [Managed service](https://docs.xtrace.ai/x-vec/managed-service.md): XTraceIntegration is the single entry point for the XTrace API — security model, connecting, loading, querying, metadata search, chunk operations, and execution context management. - [Metadata filtering](https://docs.xtrace.ai/x-vec/metadata-filtering.md): Filter encrypted search by plaintext metadata tags — field schema, supported operators, query examples, and the privacy trade-offs. - [Quickstart](https://docs.xtrace.ai/x-vec/quickstart.md): A complete end-to-end walkthrough of the x-vec Python SDK — create an execution context, encrypt and store documents, and run an encrypted search. ## OpenAPI Specs - [openapi.public](https://api.staging.xtrace.ai/openapi.public.json) - [openapi](https://docs.xtrace.ai/api-reference/openapi.json)