Agentmemory Mcp Tools

Name: Agentmemory Mcp Tools
Author: rohitg00

rohitg00/agentmemory

6.4k installs
26.6k repo stars
Updated August 3, 2026
rohitg00/agentmemory

agentmemory-mcp-tools is an agent skill: 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 argu

About

The agentmemory-mcp-tools skill indexes every agentmemory MCP tool with parameters and selection guidance. Quick start saves with memory_save using content, concepts, and files, then recalls via memory_smart_search for hybrid BM25, vector, and graph-expanded search. Tool families span capture, retrieve, sessions, commits, lessons, graph queries, structured slots, and governance utilities like memory_audit and memory_heal. Workflow guidance prefers memory_smart_search for open recall, memory_recall for focused queries, and memory_sessions for listings. Agents must read generated REFERENCE.md for exact parameter names because REST handlers whitelist fields and drop unknown keys. Cross-links cover rest-api, config, and user-invocable action skills including remember, recall, recap, and handoff that wrap the most common operations for day-to-day agent memory tasks in coding workflows. Agents should read SKILL.md quick start steps, verify required binaries and environment variables, and follow reference files for exact parameters before calling tools.

Covers agentmemory-mcp-tools quick start, workflow steps, and reference pointers from SKILL.md.
Tagged for stage build and subphase agent-tooling in the closed Skillselion taxonomy.
Documents prerequisites, permissions apis, and compatible agents.
Includes AEO tagMeta with task queries, keywords, and evidence quotes for discovery.
Cross-links related skills and generated REFERENCE.md tables where the repo provides them.

Agentmemory Mcp Tools by the numbers

6,406 all-time installs (skills.sh)
+658 installs in the week ending Aug 5, 2026 (Skillselion tracking)
Ranked #121 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
Data as of Aug 5, 2026 (Skillselion catalog sync)

At a glance

agentmemory-mcp-tools capabilities & compatibility

Capabilities: agentmemory mcp tools documented workflow · quick start examples · reference parameter lookup · taxonomy aligned metadata · aeo discovery fields
Use cases: memory · orchestration

From the docs

What agentmemory-mcp-tools says it does

Map of every agentmemory MCP tool, what each does, and its parameters. Use when choosing which memor

SKILL.md

npx skills add https://github.com/rohitg00/agentmemory --skill agentmemory-mcp-tools

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Installs	6.4k
repo stars	★ 26.6k
Last updated	August 3, 2026
Repository	rohitg00/agentmemory ↗

How do I run agentmemory-mcp-tools correctly without guessing steps, tools, or parameters?

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

Who is it for?

Teams using agentmemory-mcp-tools when SKILL.md triggers match the user request.

Skip if: Skip when the task is outside agentmemory-mcp-tools documented triggers or sibling skill scope.

When should I use this skill?

User mentions agentmemory-mcp-tools, related trigger phrases, or asks to follow this SKILL.md workflow.

What you get

Completed agentmemory-mcp-tools workflow with outputs and checks defined in SKILL.md.

agentmemory-mcp-tools output per SKILL.md

By the numbers

Stage build/agent-tooling
Category AI & Agent Building
Complexity intermediate

Files

SKILL.mdMarkdownGitHub ↗

agentmemory exposes its full capability set as MCP tools. This skill is the index: it tells you which tool to reach for and where to find exact parameters.

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 and limit to retrieve it later. This runs hybrid BM25 plus vector plus graph-expanded search.

Tool families

Capture: memory_save, memory_observe flows, memory_compress_file.
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.

Reference

Full tool table with parameters and the core-set marking lives in REFERENCE.md, generated from source so it never drifts.

agentmemory MCP tools reference

Generated from src/mcp/tools-registry.ts. Do not edit the block below by hand; run npm run skills:gen after changing the registry.

agentmemory exposes 53 MCP tools. 8 are in the lean core set (--tools core or AGENTMEMORY_TOOLS=core); the rest load with --tools all (default).

Tool	Core	Parameters	Purpose
`memory_action_create`		`title`*: string, `description`: string, `priority`: number, `project`: string, `tags`: string, `parentId`: string, `requires`: string	Create an actionable work item with typed dependencies. Actions track what agents need to do and how work items relate to each other.
`memory_action_update`		`actionId`*: string, `status`: string, `result`: string, `priority`: number	Update an action's status, priority, or details. Set status to 'done' to complete it and unblock dependent actions.
`memory_audit`		`operation`: string, `limit`: number	View the audit trail of memory operations.
`memory_checkpoint`		`operation`*: string, `name`: string, `checkpointId`: string, `status`: string, `type`: string, `linkedActionIds`: string	Create or resolve an external checkpoint (CI result, approval, deploy status) that gates action progress.
`memory_claude_bridge_sync`		`direction`*: string	Sync memory state to/from Claude Code's native MEMORY.md file.
`memory_commit_lookup`		`sha`*: string	Look up the agent session(s) that produced a specific git commit, given its SHA. Returns the commit metadata and linked sessions.
`memory_commits`		`branch`: string, `repo`: string, `limit`: number	List recent commits linked to agent sessions, optionally filtered by branch or repo.
`memory_compress_file`		`filePath`*: string	Compress a markdown file to reduce token usage while preserving headings, URLs, and code blocks. Creates a .original.md backup before writing.
`memory_consolidate`	yes	`tier`: string	Run the 4-tier memory consolidation pipeline (working -> episodic -> semantic -> procedural).
`memory_crystallize`		`actionIds`*: string, `project`: string, `sessionId`: string	Compress completed action chains into compact crystal digests using LLM summarization. Extracts narrative, key outcomes, files affected, and lessons.
`memory_diagnose`	yes	`categories`: string	Run health checks across all subsystems (actions, leases, sentinels, sketches, signals, sessions, memories, mesh). Identifies stuck, orphaned, and inconsistent state.
`memory_export`		none	Export all memory data as JSON.
`memory_facet_query`		`matchAll`: string, `matchAny`: string, `targetType`: string	Query targets by facet tags with AND/OR logic. Find all actions tagged priority:urgent AND team:backend.
`memory_facet_tag`		`targetId`: string, `targetType`: string, `dimension`: string, `value`: string	Attach a structured tag (dimension:value) to an action, memory, or observation for multi-dimensional categorization.
`memory_file_history`		`files`*: string, `sessionId`: string	Get past observations about specific files.
`memory_frontier`		`project`: string, `agentId`: string, `limit`: number	Get all unblocked actions ranked by priority and urgency. Returns the frontier of actionable work with no unsatisfied dependencies.
`memory_governance_delete`		`memoryIds`*: string, `reason`: string	Delete specific memories with audit trail.
`memory_graph_query`		`startNodeId`: string, `nodeType`: string, `maxDepth`: number, `query`: string	Query the knowledge graph for entities and relationships.
`memory_heal`		`categories`: string, `dryRun`: string	Auto-fix all fixable issues found by diagnostics. Unblocks stuck actions, expires stale leases, cleans up orphaned data.
`memory_insight_list`		`project`: string, `minConfidence`: number, `limit`: number	List synthesized insights, higher-order observations derived from patterns across memories, lessons, and crystals.
`memory_lease`		`actionId`: string, `agentId`: string, `operation`*: string, `result`: string, `ttlMs`: number	Acquire, release, or renew an exclusive lease on an action. Prevents multiple agents from working on the same thing.
`memory_lesson_recall`		`query`*: string, `project`: string, `minConfidence`: number, `limit`: number	Search lessons by query. Returns lessons sorted by confidence and recency. Use to check what the agent has learned before making decisions.
`memory_lesson_save`	yes	`content`*: string, `context`: string, `confidence`: number, `project`: string, `tags`: string	Save a lesson learned from this session. Lessons have confidence scores that strengthen when reinforced and decay when not used. Duplicate content auto-strengthens the existing lesson.
`memory_mesh_sync`		`peerId`: string, `direction`: string	Sync memories and actions with peer agentmemory instances for multi-agent collaboration.
`memory_next`		`project`: string, `agentId`: string	Get the single most important next action to work on. Combines dependency resolution, priority, and recency into a score.
`memory_obsidian_export`		`vaultDir`: string, `types`: string	Export memories, lessons, and crystals as Obsidian-compatible Markdown files with YAML frontmatter and wikilinks for graph view.
`memory_patterns`		`project`: string	Detect recurring patterns across sessions.
`memory_profile`		`project`*: string, `refresh`: string	User/project profile with top concepts and file patterns.
`memory_recall`	yes	`query`*: string, `limit`: number, `format`: string, `token_budget`: number	Search past session observations for relevant context. Use when you need to recall what happened in previous sessions, find past decisions, or look up how a file was modified before.
`memory_reflect`	yes	`project`: string, `maxClusters`: number	Traverse the knowledge graph, group related memories by concept clusters, and synthesize higher-order insights via LLM. Returns new and reinforced insights.
`memory_relations`		`memoryId`*: string, `maxHops`: number, `minConfidence`: number	Query the memory relationship graph.
`memory_routine_run`		`routineId`*: string, `project`: string, `initiatedBy`: string	Instantiate a frozen workflow routine, creating actions for each step with proper dependencies.
`memory_save`	yes	`content`*: string, `type`: string, `concepts`: string, `files`: string, `project`: string	Explicitly save an important insight, decision, or pattern to long-term memory.
`memory_sentinel_create`		`name`: string, `type`: string, `config`: string, `linkedActionIds`: string, `expiresInMs`: number	Create an event-driven sentinel that watches for conditions (webhook, timer, threshold, pattern, approval) and auto-unblocks gated actions when triggered.
`memory_sentinel_trigger`		`sentinelId`*: string, `result`: string	Externally fire a sentinel, providing an optional result payload. Unblocks any gated actions.
`memory_sessions`	yes	none	List recent sessions with their status and observation counts.
`memory_signal_read`		`agentId`*: string, `unreadOnly`: string, `threadId`: string, `limit`: number	Read messages for an agent. Marks delivered messages as read.
`memory_signal_send`		`from`: string, `to`: string, `content`: string, `type`: string, `replyTo`: string	Send a message to another agent or broadcast. Supports threading, typed messages, and TTL expiration.
`memory_sketch_create`		`title`*: string, `description`: string, `expiresInMs`: number, `project`: string	Create an ephemeral action graph for exploratory work. Auto-expires after TTL. Can be promoted to permanent actions or discarded.
`memory_sketch_promote`		`sketchId`*: string, `project`: string	Promote a sketch's ephemeral actions to permanent actions. Makes the exploratory work official.
`memory_slot_append`		`label`: string, `text`: string	Append text to an existing slot. Fails with 413 if the append would exceed the slot's sizeLimit, agent must compact via memory_slot_replace first.
`memory_slot_create`		`label`*: string, `content`: string, `sizeLimit`: number, `description`: string, `pinned`: string, `scope`: string	Create a new slot. Reject if a slot with the same label already exists.
`memory_slot_delete`		`label`*: string	Delete a slot. Seeded default slots can be deleted unless marked readOnly.
`memory_slot_get`		`label`*: string	Read a single slot by label.
`memory_slot_list`		none	List all memory slots (pinned + project + global). Slots are editable, size-limited memory units the agent can read and modify across sessions.
`memory_slot_replace`		`label`: string, `content`: string	Replace slot content in place. Fails if content exceeds sizeLimit.
`memory_smart_search`	yes	`query`*: string, `expandIds`: string, `limit`: number	Hybrid semantic+keyword search with progressive disclosure.
`memory_snapshot_create`		`message`: string	Create a git-versioned snapshot of current memory state.
`memory_team_feed`		`limit`: number	Get recent shared items from all team members.
`memory_team_share`		`itemId`: string, `itemType`: string	Share a memory or observation with team members.
`memory_timeline`		`anchor`*: string, `project`: string, `before`: number, `after`: number	Chronological observations around an anchor point.
`memory_verify`		`id`*: string	Verify a memory or observation by tracing its citation chain back to source observations and session context. Returns provenance information including confidence scores.
`memory_vision_search`		`queryText`: string, `queryImageRef`: string, `queryImageBase64`: string, `topK`: number, `sessionId`: string	Cross-modal image search via CLIP embeddings. Pass queryText to find screenshots matching a description, or queryImageBase64/queryImageRef to find similar images. Requires AGENTMEMORY_IMAGE_EMBEDDINGS=true.