> ## Documentation Index > Fetch the complete documentation index at: https://docs.xynthis.com/llms.txt > Use this file to discover all available pages before exploring further. # MCP integration > Use Xynthis memory from Claude Code, Cursor, Codex, or any MCP client via the xynthis-mcp bridge. `xynthis-mcp` is a stdio MCP server that gives any MCP client (Claude Code, Cursor, Codex) direct access to the brain. The client launches it as a child process; each tool call becomes one request over the brain's unix socket at `~/.xynthis/brain.sock`. No new editor, no separate daemon of its own, but the brain must be running, which the installer sets up at login. ## Registration The binary ships in `~/.xynthis/bin/`. For Claude Code: ```bash theme={null} claude mcp add xynthis -- ~/.xynthis/bin/xynthis-mcp ``` For Cursor, Codex, or any client that reads a JSON config, add the server block: ```json theme={null} { "mcpServers": { "xynthis": { "command": "xynthis-mcp", "args": [] } } } ``` (`.mcp.json` in a project root for Claude Code; `~/.cursor/mcp.json` for Cursor.) Use the full path if `~/.xynthis/bin` is not on the PATH the client inherits. Tools appear under the `mcp__xynthis__` prefix. Every tool response is capped by a per-tool byte budget (60 KB default) before it reaches the client, so a fat recall can't blow through the model's context window. Truncated responses carry a `[budget:...]` footer. ## Tools ### Memory | Tool | What it does | | ---------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `remember` | Store a perception (`content`, optional `kind` tag: `user_msg`, `tool_use`, `file_edit`, `decision`, `insight`). Consolidated into long-term storage on the next dream cycle | | `recall` | Layered retrieval: identity, working memory, knowledge graph, then binary rescore. Takes `query` and optional `top_k` (default 8 per layer); reports which layers fired | | `brief` | One-shot session brief: a compact markdown block with the user's identity, top-ranked stored facts, and brain counters. Takes no arguments; call it first in every session | | `kg_add` | Add a temporal fact as a (subject, predicate, object) triple with optional `valid_from`/`valid_until` bounds and `confidence` | | `kg_query` | Query the graph by `entity`, `predicate`, and/or `as_of_secs`; all filters are optional, and entity matches subject or object | `brief` is the recommended session opener. It fans out four brain ops concurrently: identity, profile, recall (`top_k` 40), and status. The facts block comes primarily from the server-side `profile` op, a grounded projection of remembered facts; recall supplies the recent working-memory ring and fills the facts block only when the profile projection is empty. Confirmed facts render with a signed marker. ### Corpus and code | Tool | What it does | | -------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `corpus_add` | Index a folder as a named corpus (`path`, optional `name`, `mask` glob, `chunk_strategy` of `auto`/`regex`, `watch` default true). Returns immediately; indexing runs in the background, so poll `corpus_list` | | `corpus_list` | List indexed corpora with size, context, and watch state | | `corpus_update` | Re-index a collection (BLAKE3 dedup skips unchanged chunks); omit `name` for all | | `corpus_context_set` | Attach a description that travels with every recall hit from that collection | | `code_scan` | Structurally scan a repo (Rust / TypeScript / Python / Go / Swift, tree-sitter, respects .gitignore) into typed `code:*` triples. Query afterward with `kg_query`, e.g. `kg_query(entity='code:::src/lib.rs')` | ### Watchers | Tool | What it does | | ---------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `watcher_create` | Create a polled event watcher. Providers: `files_changed` (new/modified files under a root) and `command_output` (run a read-only command, fire when its stdout hash changes). Minimum interval 15 seconds. Events become `watcher_event` perceptions that recall surfaces | | `watcher_list` | List watchers with last-run / last-event timestamps | | `watcher_delete` | Delete a watcher by id | ### Witnessed memory | Tool | What it does | | ------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `confirm` | Cryptographically attest a recalled fact is correct: signs it with the local Ed25519 identity and appends to the Merkle log at `~/.xynthis/bmc/witness.log`. Takes `fact_id` from a prior recall hit | | `why_witness` | Full audit view for a confirmed fact: signed payload, signature, RFC-6962 inclusion proof, offline-verifiable against the public key alone | ### Introspection and learning | Tool | What it does | | ---------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `identity` | Snapshot of mood, interaction count, consolidation score, and the six-axis personality vector | | `status` | Brain state: uptime, perceptions, last dream, working-memory size, knowledge-graph size | | `dream` | Force a consolidation cycle now. Use sparingly; the gates fire automatically | | `learner_status` | The online rerank learner's training step count, samples seen, last loss, and weights | | `train_step` | Force one training step on the rerank head. Debugging aid; the learner runs its own background loop | | `skill_status` | The per-user skill model: checkpoint state, score-call counts, training-row count | | `skill_train` | Run the skill-model trainer once and return its summary | | `llm_status` | The on-device model's training state from `~/.xynthis/llm/state.json`: cumulative steps, last loss, latest checkpoint. Reads the file directly, so it works even when the brain is down | | `llm_train_set` | Control the on-device training loop: `enabled` on/off, `interval_secs` (60-86400), `force_tick` to run one training pass now. Writes `~/.xynthis/llm/train_config.json`, which the model server polls every 5 seconds | ## Failure modes If the brain is not running, tool calls fail with a JSON-RPC error (`-32000`) rather than hanging; there is no retry. `xynthis health` from a terminal confirms the stack is up. `llm_status` and `llm_train_set` are the exceptions: they are file-backed and work without the brain. `~/.xynthis/llm/state.json` exists after the first `xynthis-llm-serve` start: the server writes an initial status snapshot at boot, before any training runs. To enable training, write `train_config.json` via `llm_train_set` or the app's settings.