cogmemai-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| COGMEMAI_API_KEY | Yes | Your API key (starts with cm_) | |
| COGMEMAI_API_URL | No | Custom API URL (default: hifriendbot.com) | hifriendbot.com |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| save_memoryB | Store a developer memory (fact, preference, decision, architecture detail). Memories persist across all Claude Code sessions and are available in future conversations. |
| save_ruleA | Save a mandatory rule that will ALWAYS be followed in every session. Rules bypass scoring and decay — they are injected into every conversation, every time. Use for absolute requirements like "NEVER do X" or "ALWAYS do Y". |
| list_rulesA | List all mandatory rules for the current project and/or globally. Rules are always-on memories that surface in every session. |
| delete_ruleA | Delete a mandatory rule by its memory ID. Use list_rules to find the ID first. |
| preflightA | Think Before You Speak. Call this BEFORE making any suggestion, recommendation, or action plan. Sends the topic to a fast keyword search and returns any relevant prior context — previous attempts, decisions, contacts, evaluations. This prevents suggesting things that were already tried, rejected, or completed. Fast and cheap — use liberally. |
| recall_memoriesA | Search stored memories using semantic search. Returns memories ranked by relevance, importance, and recency. Use this to find relevant context from past sessions. |
| extract_memoriesA | Extract memories from a conversation exchange using AI. Send the developer message and assistant response, and the server identifies facts worth remembering (architecture decisions, preferences, bug fixes, etc.). |
| get_project_contextA | Load top memories for the current project plus relevant global memories. Use at the start of a session to get full context from previous sessions. Optionally pass context to get memories most relevant to your current task. |
| list_memoriesB | List stored memories with optional filters by type, category, scope, or project. |
| delete_memoryA | Delete a specific memory by its ID. This is permanent. |
| update_memoryC | Update an existing memory's content, importance, or scope. |
| bulk_deleteA | Delete multiple memories at once by their IDs. Maximum 100 IDs per call. This is permanent. |
| bulk_updateA | Update multiple memories at once. Each item needs a memory_id and fields to update. Maximum 50 items per call. |
| get_usageA | Get current usage statistics — memory count, extractions this month, tier info, projects. |
| export_memoriesA | Export all memories as JSON. Use this to back up memories or transfer them to another project. |
| import_memoriesA | Bulk import memories from a JSON array. Each memory needs at minimum a content field. Deduplication is applied automatically. |
| ingest_documentA | Extract memories from a document by splitting it into chunks and processing each one. Great for onboarding — feed in READMEs, architecture docs, or API specs to quickly build project context. |
| save_session_summaryB | Save a summary of the current coding session. Captures what was accomplished, decisions made, and next steps. Stored as a session_summary memory for future reference. |
| list_tagsA | List all tags in use across your memories, with counts. Use this to see what threads/groups exist and find related memories by tag. |
| link_memoriesA | Connect two related memories with a named relationship. Use this to build a knowledge graph — e.g., linking a bug fix to the architecture decision that caused it, or connecting a preference to the pattern it led to. |
| get_memory_linksA | View all memories linked to a specific memory. Returns the relationship type and full memory details for each connection. Use this to explore the knowledge graph around a memory. |
| get_memory_versionsA | View the edit history of a memory. Shows all previous versions with timestamps and what changed. Useful for understanding how a decision or fact evolved over time. |
| get_analyticsA | Get a memory health dashboard with insights: most recalled memories, never-recalled memories, stale memories, growth trends, and breakdowns by type and category. Use this to identify cleanup opportunities and understand memory usage patterns. |
| promote_memoryA | Promote a project-scoped memory to global scope so it applies across all projects. Use this when you discover a preference or pattern that should be universal — e.g., "user prefers tabs over spaces" or "always use Bun instead of npm". |
| consolidate_memoriesA | Consolidate related memories into fewer, richer memories. Finds clusters of memories sharing the same subject (3+ memories required), then uses AI to synthesize each cluster into 1-2 comprehensive facts. Originals are archived (not deleted) with full version history. Use dry_run=true to preview without making changes. Great for cleaning up memory clutter after many sessions. |
| save_taskB | Create a task that persists across sessions. Tasks are tracked with status (pending, in_progress, done, blocked) and priority (high, medium, low). Use this to maintain continuity on multi-session work. |
| get_tasksA | Get tasks for the current project. Returns tasks filtered by status — defaults to showing pending and in_progress tasks. Use at session start to pick up where you left off. |
| update_taskA | Update a task's status, title, description, or priority. Use this to mark tasks as in_progress, done, or blocked as you work. |
| save_correctionA | Save a correction pattern — what went wrong and what the right approach is. These are surfaced automatically when similar situations arise in future sessions, helping avoid repeated mistakes. |
| set_reminderA | Set a reminder that surfaces automatically at the start of your next session. Use for follow-ups, things to check, or deferred work. Reminders auto-archive after being shown. |
| get_stale_memoriesA | Find memories that may be outdated based on age and access patterns. Returns memories that haven't been recalled or updated recently, so you can review, update, or delete them. |
| get_file_changesA | Show what files changed since your last session. Compares the current git state to a snapshot saved when your previous session ended. Helps you understand what happened between sessions. |
| feedback_memoryA | Signal whether a recalled memory was useful or irrelevant. Helps improve future recall quality over time. Use after recalling memories to indicate which were helpful vs noise. |
| generate_skillsA | Manually trigger skill generation from your corrections, preferences, and patterns. Skills are behavioral directives that auto-improve how the AI works with you. CogmemAi also generates skills automatically when enough evidence accumulates — this tool lets you trigger it manually or preview candidates. |
| extract_principlesB | Analyze memory clusters and extract underlying factual principles or patterns. Principles are observations about your project — "this codebase tends to have X" — not behavioral instructions (those are skills). Use dry_run to preview candidates first. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
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