local-brain-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| brain_recallA | Semantically search your local codebase memory across all agents. Returns the most relevant lessons, bug fixes, architecture decisions, and conventions from your git history and AI sessions — filtered to current file and package scope. Results are ranked deterministically with validation boost and contradiction penalties, token-capped to stay within 250 tokens. |
| brain_statusA | Get system diagnostics, memory statistics, multi-agent breakdown, and validation health. Returns total memory count, breakdown by agent, validation counts, contradiction flags, and database storage path. |
| brain_learnA | Store a new durable lesson, architecture decision, bug root-cause, or team convention. Includes automatic multi-agent attribution, quality evaluation, deduplication, contradiction detection, and supersession tracking. Examples: "Never use RS256 in dev", "JWT refresh token expires in 7d; rotate on each use". |
| brain_validateA | Validate that an existing memory was helpful and correct in the current session. Increments the memory validation count, records the validating agent, and boosts confidence. |
| brain_traceA | Show all memory entries associated with a specific file across all agents. Returns the full fix history, architecture decisions, past bugs, and agent attribution for that file in chronological order. Includes confidence and status flags. |
| brain_forgetA | Remove or deprecate specific memories from Local Brain. Can target a memory by ID, file path, or search query. By default deprecates the memory to maintain audit trail; pass hard_delete: true to purge. |
| brain_pruneA | Clean up stale or deprecated memories from the brain. Run this after major refactors to prevent outdated context from polluting recalls. Optionally runs the full git-diff invalidation pass to detect modified/deleted files. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 7 tools
Most tools have clearly distinct purposes: learn, recall, validate, status, and trace are easy to tell apart. However, brain_prune and brain_forget both involve removing memories, and brain_recall and brain_trace both retrieve memories, so an agent could occasionally hesitate between them.
All tool names follow the same brain_ prefix plus a lowercase verb pattern, such as brain_learn, brain_recall, and brain_forget. The naming is highly consistent and predictable.
Seven tools is a well-scoped size for a local memory management server. Each tool covers a meaningful operation without bloat, and the count feels appropriate for the domain.
The tool set covers the core memory lifecycle: create (brain_learn), read (brain_recall, brain_trace, brain_status), validate (brain_validate), and delete/deprecate (brain_forget, brain_prune). There is no direct way to edit an existing memory's content, but forgetting and relearning can work around that gap.