distill-mcp-v2
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| HOST | No | The host to bind the server to. | 0.0.0.0 |
| PORT | No | The port to listen on. | 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 | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| distill_jsonB | Compress JSON structures by collapsing large arrays and metadata while preserving error fields. Supports iterative budget-based compression. |
| distill_logsB | Filter and compress raw logs by preserving startup context, shutdown state, and matching error traces while omitting large blocks of repetitive status messages. |
| distill_schemaA | Reduce token overhead of MCP tool schemas or JSON Schemas. Strips descriptions/examples (compact mode) or collapses to parameter names/types (minimal mode). |
| distill_responseC | Progressively compress any generic tool response (JSON, HTML, or text) to fit within a specific token budget. |
| distill_conversationA | Extract a high-level briefing (goals, decisions, errors, current state, pending tasks) from a conversational message trace (JSON array or raw text) to fit within a token budget. |
| stabilize_for_cacheA | Normalize dynamic elements like UUIDs, timestamps, and hex IDs to sequential placeholders, maximizing provider-level prompt caching hit rates. |
| analyze_tokensA | Count tokens using model-aware tokenizers and estimate API costs across multiple configured models. |
| compareB | Generate comparison metrics (token count reduction, compression ratio, cost savings) between uncompressed and distilled text formats. |
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 8 tools
Each tool targets a specific input type or operation: token analysis, comparison, distillation for conversations/JSON/logs/responses/schemas, and cache stabilization. No two tools have overlapping purposes.
Most tools follow a consistent verb_noun pattern (e.g., distill_conversation, distill_json). The tool 'compare' is a verb-only exception, but it is still clear and fits the domain.
With 8 tools, the server covers token analysis, multiple distillation formats, comparison metrics, and cache optimization. This is well-scoped for the stated purpose without being excessive or insufficient.
The tool surface provides comprehensive coverage for the domain of token optimization and compression: cost estimation, multi-format distillation, schema reduction, and caching normalization. No obvious gaps are evident.