Skip to main content

agentmemory-mcp-tools

Map of every agentmemory MCP tool, what each does, and its parameters. Use when choosing which memory tool to call, when a tool name or argument is unclear, or when answering what agentmemory can do via MCP.

ソース情報

リポジトリ
rohitg00/agentmemory
ソースの最終更新活動
2026年10月25日 11:40
検出された SKILL.md の言語
英語
スター
29,991
フォーク
2,649

インストール方法

デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。

ソースファイルを確認

インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。

ファイルエクスプローラー
3 ファイル

SKILL.md を表示中

SKILL.md
ソースの指示 · 読み取り専用プレビュー
name
agentmemory-mcp-tools
description
Map of every agentmemory MCP tool, what each does, and its parameters. Use when choosing which memory tool to call, when a tool name or argument is unclear, or when answering what agentmemory can do via MCP.
user-invocable
false
This skill indexes agentmemory's MCP tools. Use the connected server's tool inventory and schemas; a native memory provider may expose a smaller set under different names. Hermes and OpenClaw skills that need the full surface require a separate MCP connection to the running daemon. For Pi and OMP, connect with `--with-mcp` to enable the broader workflows. Pi exposes MCP names with an `mcp__agentmemory__` prefix; OMP exposes MCP operations as `xd://mcp__agentmemory_<tool>` devices through its `write` tool. ## Quick start Save then recall: 1. `memory_save` with `content` (the insight), `concepts` (comma-separated keywords), `files` (comma-separated paths). 2. `memory_smart_search` with `query`, `limit`, and `targetLayer: "memory"` to retrieve saved knowledge later. Omit `targetLayer` to also search captured observations. This runs hybrid BM25 plus vector plus graph-expanded search. ## Tool families - Capture: `memory_save`, `memory_compress_file`. Automatic observations use native hooks or `POST /agentmemory/observe`, not an MCP observation tool. - Retrieve: `memory_smart_search`, `memory_recall`, `memory_file_history`, `memory_timeline`, `memory_vision_search`. - Sessions and commits: `memory_sessions`, `memory_commits`, `memory_commit_lookup`. - Knowledge and graph: `memory_lesson_save`, `memory_lesson_recall`, `memory_graph_query`, `memory_relations`, `memory_patterns`, `memory_crystallize`. - Structured slots: `memory_slot_create`, `memory_slot_append`, `memory_slot_get`, `memory_slot_list`, `memory_slot_replace`, `memory_slot_delete`. - Governance and health: `memory_governance_delete`, `memory_audit`, `memory_verify`, `memory_heal`, `memory_diagnose`. ## Workflow 1. Pick the narrowest tool for the task. Prefer `memory_smart_search` for open recall, `memory_recall` when you already have a focused query, `memory_sessions` for session listings. 2. Look up exact parameter names and which are required in REFERENCE.md before calling. 3. Pass only documented fields. REST handlers whitelist fields and drop unknown ones. 4. For budgeted `memory_recall`, distinguish `matched_count: 0` from `excluded_by_budget > 0`. Expand clipped or omitted IDs with `memory_smart_search` and `expandIds`, preserving the same scope filters. ## See also - agentmemory-rest-api for the HTTP equivalents. - agentmemory-config for tool-visibility and feature flags. - The user-invocable action skills (remember, recall, recap, handoff, forget) wrap the most common tools. ## Reference Full tool table with parameters and the core-set marking lives in REFERENCE.md, generated from source so it never drifts.
GitHubで見る