Agent Memory
Recall past mistakes and capture feedback so your agent stops repeating errors. Works locally via MCP server — no API key needed.
Agent Memory
Give your agent persistent memory across sessions. Before starting any task, recall what went wrong last time. After completing work, capture whether it succeeded or failed. Prevention rules are auto-generated from repeated mistakes.
Setup
Add the MCP server (one-time):
claude mcp add thumbgate -- npx -y thumbgate serve
No API key needed. All data stays local.
When to Use
- Starting a new task or session — recall past context first
- After completing work that succeeded or failed — capture feedback
- When the agent keeps making the same mistake — check prevention rules
Workflow
Step 1: Recall past context (do this FIRST on every task)
Call the recall MCP tool with a description of your current task. The tool returns:
- Past feedback relevant to this task (vector similarity search)
- Active prevention rules (auto-generated from repeated failures)
- Recent feedback summary with approval rate
Read the prevention rules carefully. These are patterns that failed before — follow them.
Step 2: Do your work
Complete the task as normal. Keep track of what you did and whether it worked.
Step 3: Capture feedback
Call the capture_feedback MCP tool:
If succeeded:
- signal:
up - context: What worked and why
- tags: Category labels
If failed:
- signal:
down - context: What you were trying to do
- whatWentWrong: Specific failure description
- whatToChange: How to avoid this next time
- tags: Category labels
Vague feedback like "it failed" will be rejected. Be specific.
Step 4: Check improvement (optional)
Call the feedback_stats MCP tool to see approval rate, top failure domains, and whether the agent is trending better or worse.
Available MCP Tools
| Tool | What it does |
|---|---|
recall | Search past feedback and prevention rules for current task |
capture_feedback | Record what worked or failed with structured context |
prevention_rules | View auto-generated rules from repeated mistakes |
feedback_stats | Approval rate, trend analysis, top failure domains |
feedback_summary | Human-readable summary of recent signals |
MCP Profiles
| Profile | Tools | Use case |
|---|---|---|
essential | 5 core tools | Default — start here |
commerce | 6 tools + commerce_recall | Agentic commerce agents |
default | 12 tools | Full pipeline including DPO export |
Set profile: THUMBGATE_MCP_PROFILE=essential npx thumbgate serve
How Prevention Rules Work
- Agent makes mistake A → you capture
downfeedback - Agent makes mistake A again → you capture
downfeedback again - System detects pattern → auto-generates prevention rule: "NEVER do A"
- Next session →
recallreturns the rule → agent follows it
This is the core value. The agent doesn't learn — but it reads the rules and follows them.