compresh-mcp 0.2.0

MCP server for Compresh — production-grade context compression with Q-protective ranking, epistemic markers, and depth-aware adaptation

compresh-mcp

MCP server for Compresh — production-grade context compression for LLM agent conversations.

Compresh adds Q-protective ranking, epistemic marker classification, and depth-aware adaptation on top of the open-source tulbase compression core. This is the paid tier distribution.

Architecture (0.2.0+)

• Local: bundled tulbase (MIT, vendored as compresh_mcp.tulbase) runs on every turn for fast compression + cold-storage support (fetch_compressed / list_compressed MCP tools).
• Server: TUL 1.0 layers (Q-protective ranking, epistemic markers, semantic store) run on Compresh infrastructure via the /v1/tul1 endpoint, gated by your Compresh API key + tier.
• Degraded mode: if /v1/tul1 is unreachable, compresh-mcp transparently falls back to the local tulbase result so compression never blocks.

Previously (0.1.0, yanked), TUL 1.0 classifiers shipped inside the client package. That distribution leaked paid features into the local install and is no longer recommended — install 0.2.0 or later. See CHANGELOG.md for the migration note.

What's the difference vs tulbase-mcp?

Feature	tulbase-mcp (free, open-source)	compresh-mcp (paid)
Base LexRank summarization	✅	✅
Modality elision (code, terminal, JSON, stack traces)	✅	✅
Cold storage + fetch_compressed	✅	✅
Protection Zone (Claim 1e)	✅	✅
Q-protective sentence ranking (Q1–Q4 categorization)	❌	✅
Epistemic markers (VR/HR/CR/UC)	❌	✅
Semantic store (cross-turn Q3 dedup)	❌	✅
Saving telemetry to Compresh dashboard	❌	✅
Multi-device sync (planned)	❌	✅

In Compresh's bench (Compresh-bench v1, 600-turn multi-model), Q-protective ranking adds 5–12 percentage points of equivalence preservation vs base LexRank at the same token savings — Pareto improvement.

Pricing

See https://compre.sh/pricing. Three tiers:

• Tier-A (integrated MCP/OAuth metadata, e.g. Cowork, Claude Code, Cursor): saving-share %25 on actual model cost
• Tier-B (family-level provider declaration): saving-share %25 on the family's cheapest model price
• Tier-C (anonymous / local LLM / free models): flat $0.20 per 1M saved input tokens

Every new user: $30 free credit (90-day expiry), $10 minimum budget (charged $7.5 after standard %25 discount).

Installation

pip install compresh-mcp

On first run, you'll be prompted for your Compresh API key. If you don't have an account, your browser opens to compre.sh/signup automatically.

MCP client configuration

Claude Code (~/.claude/mcp.json)

{
  "mcpServers": {
    "compresh": {
      "command": "compresh-mcp",
      "env": {
        "COMPRESH_API_KEY": "sk-comp_...",
        "COMPRESH_API_BASE": "https://api.compre.sh"
      }
    }
  }
}

Cursor (~/.cursor/mcp.json)

Same structure as Claude Code.

Cowork

Cowork → Settings → Tools → MCP servers → Add:

• Command: compresh-mcp
• Environment: COMPRESH_API_KEY=sk-comp_...

Tools exposed

Same four tools as tulbase-mcp, with enhanced behavior:

• compress — Q-protective compression by default (protection_mode="balanced")
• fetch_compressed, list_compressed, stats — same interface

Plus paid-tier extras:

• usage — current cycle budget, free credit balance, savings metrics

License

Business Source License 1.1 — see LICENSE. Production use permitted with valid Compresh API key. License automatically converts to MIT after 4 years (Year 2030).

Patents

Q-protective sentence ranking + Protection Zone are covered by TR-TPMK patent application 2026/007305 (Compresh Ltd, May 2026). A valid Compresh subscription grants implementation license.

Status

v0.1.0 — first public release, May 2026. Active development. APIs may change before v1.0. Issues and pull requests welcome.

Links

• compre.sh — product site
• Documentation — full reference
• GitHub — source
• Issues — bug reports
• tulbase (open core, MIT) — standalone