Reference

Tool Reference

All 35 MCP tools that your AI auto-discovers when connected to MemQ.


Validate the tool loop with a starter

The quickest validation is not reading the full tool list. It is saving one decision, starting a fresh request, and recalling it through search_memory.

Recommended starter

Minimal MCP memory setup with a save, restart, and recall continuity test.

Open memq-mcp-starter · quickstart


Tools by customer job

Use this map when you want outcomes instead of tool names. MemQ provides governed memory for remembering, finding, reflecting, sharing, and verifying.

Remember

Store decisions, facts, code patterns, and checkpoints.

add_memorysave_contextjournal_recordslicer_slice

Find

Retrieve the right context without rereading the whole project.

query_memorysearch_memoryrecent_memorybrain_recall_episode

Reflect

Turn repeated work into reusable procedures and corrected beliefs.

reflect_memoryjournal_distillbrain_consolidate_sleepbrain_reinforce

Share

Use team and shared knowledge without mixing private namespaces.

commons_searchcommons_resonancecommons_promotion_statusbrain_discoverbrain_associatebrain_predict

Verify

Confirm auth, namespace, health, and usage before production work.

reunionnamespace_infomemory_statushealth_checkmnemosyne_context


Core Memory

add_memory

Store a new memory entry with content and optional metadata.

When to use: When your AI learns something worth remembering — a pattern, decision, or fact.

query_memory

Retrieve memories matching a natural-language query.

When to use: When your AI needs to recall specific knowledge from past sessions.

search_memory

Full-text and semantic search across stored memories.

When to use: When you need broad search across everything stored — more exploratory than query.

recent_memory

Fetch the most recently stored memories in chronological order.

When to use: When you need context from the current or last session.

reflect_memory

Trigger a reflection pass over stored memories to surface insights.

When to use: After a series of tasks — helps the AI distill patterns from accumulated experience.


Journal

journal_record

Write a structured journal entry with mode, actor, outcome, and optional reward signal.

When to use: To log decisions, outcomes, and learning moments during a work session.

journal_search

Search journal entries by content, mode, or time range.

When to use: To recall past decisions, search for how a problem was solved before.

journal_distill

Distill journal entries into consolidated learnings — observation-aware.

When to use: After a series of sessions — compresses journal history into reusable knowledge.


Brain

brain_discover

Discover related concepts and connections in the knowledge graph.

When to use: When exploring what the AI knows about a topic and its relationships.

brain_associate

Create an explicit association between two concepts in the graph.

When to use: When you want the AI to permanently link two ideas or patterns.

brain_recall_episode

Recall a specific episode — a complete context window from a past session.

When to use: When you need the full context of a past interaction, not just a snippet.

brain_consolidate_sleep

Run a sleep-like consolidation pass — strengthens strong memories, prunes weak ones.

When to use: Periodically or at end-of-day — mimics how biological memory consolidates during sleep.

brain_reinforce

Apply reinforcement to specific memories based on outcome signals.

When to use: After completing a task — reward successful patterns, weaken unsuccessful ones.

brain_predict

Generate predictions based on learned patterns and associations.

When to use: When you want the AI to anticipate what comes next based on past experience.


Context

save_context

Checkpoint the current working context for retrieval in future sessions.

When to use: Before switching tasks or ending a session — saves your place.

mnemosyne_context

Pack maximum relevant context into the token budget using the Mnemosyne protocol.

When to use: At session start — hydrates the AI with the most relevant memories for the task.


Commons

commons_search

Search approved shared knowledge without mixing it into private memory.

When to use: When you need governed shared knowledge such as threat intel, industry news, or resolved issues.

commons_resonance

Surface hive-mind resonance and promotion candidates without bypassing runtime governance.

When to use: When you want to identify patterns that are ready for team or commons promotion.

commons_promotion_status

Read recent hosted commons promotion decisions without exposing raw private candidate text.

When to use: When you need to audit what was promoted, skipped, or rejected.

commons_retract

Admin-only retraction path for removing bad shared knowledge and writing a tombstone ledger.

When to use: When governed commons content must be redacted or retired.


System

health_check

Check the health of the MemQ service and backend connectivity.

When to use: To verify the service is running and all backends are reachable.

memory_status

Get current memory usage, access, and readiness statistics.

When to use: To check how much memory you're using and what namespaces are active.

namespace_info

Get details about the current namespace — tier, scope, permissions.

When to use: To verify which namespace you're connected to and what access you have.

reunion

Session handshake — greeting, namespace resolution, and context continuity.

When to use: At the start of every session. This is the first tool to call.


Slicer

slicer_slice

Slice content into optimally-sized chunks for memory storage.

When to use: When ingesting large documents or codebases into memory.


Common workflow patterns

Session startup

Every session
reunion              # Handshake — namespace, context continuity
mnemosyne_context    # Hydrate with relevant memories
namespace_info       # Confirm access tier

Learning loop

After completing a task
journal_record       # Log what was done, outcome, reward signal
brain_reinforce      # Strengthen successful patterns
reflect_memory       # Surface insights from accumulated experience
save_context         # Checkpoint for next session

Knowledge exploration

When researching a topic
brain_discover       # Find related concepts in the graph
brain_associate      # Link related ideas permanently
commons_search       # Search approved shared knowledge
commons_resonance    # Inspect shared-pattern and promotion signals
brain_recall_episode # Pull full context from a past session

Maintenance

Periodically
brain_consolidate_sleep  # Consolidate — strengthen strong, prune weak
journal_distill          # Compress journal into reusable knowledge
memory_status            # Check storage usage