TokenMizer
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| TOKENMIZER_URL | No | The URL of the running TokenMizer proxy server | http://localhost:8000 |
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 |
|---|---|
| checkpoint_sessionA | Save the current AI session to TokenMizer's graph memory. Creates a checkpoint that can be resumed later with full context. Use this when: finishing a work session, before switching tasks, or when the conversation is getting long. |
| resume_sessionA | Get the resume context for a previous session. Returns a compact summary of what was done, decided, and what's pending. Inject this into the system prompt when starting a new session on the same project. |
| get_graph_statsA | See the knowledge graph stats for a session: how many tasks, decisions, files, and errors are tracked. |
| analyze_fileA | Analyze a large file (CSV, Excel, PDF, JSON) and return a token-efficient summary. Instead of pasting thousands of rows into the chat, use this to get schema, statistics, and sample data in ~300-500 tokens. |
| get_savings_statsA | Get token savings analytics — how many tokens were saved today/this week. |
| why_decisionA | Reason over the session's decision history: why is something the current choice? Traces the supersession chain (old → new with trigger, reason, and evidence per hop) for decisions matching the query, and reports the currently active choice. Use when the user asks 'why did we pick X', 'what happened to Y', or 'what was the previous approach'. |
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 6 tools
Each tool targets a distinct operation: session persistence, graph statistics, file analysis, savings analytics, and decision reasoning. Even the two stats tools are clearly separated by domain (knowledge graph vs token savings).
Most names follow a clear verb_noun pattern (checkpoint_session, resume_session, analyze_file, get_graph_stats, get_savings_stats), but why_decision deviates from the verb-first convention. The mixed get_ vs bare-verb prefixes are minor and don't impede comprehension.
Six tools is appropriate for a focused session-memory and token-optimization utility. Each tool has a distinct role with no redundant entries.
The core workflows of checkpointing, resuming, analyzing files, and reviewing decisions are covered. Missing session listing/deletion and explicit decision-management operations, but agents can work around these for typical use.