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Vivesca MCP Server

by Vivesca
Developer ToolsLow Risk8.5MCP RegistryLocal
Free

Server data from the Official MCP Registry

Opinionated MCP server — Pydantic output schemas, 7 domains, built to evolve.

About

Opinionated MCP server — Pydantic output schemas, 7 domains, built to evolve.

Security Report

8.5
Low Risk8.5Low Risk

Valid MCP server (0 strong, 2 medium validity signals). 1 known CVE in dependencies ⚠️ Package registry links to a different repository than scanned source. Imported from the Official MCP Registry.

8 files analyzed · 2 issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

env_vars

Check that this permission is expected for this type of plugin.

file_system

Check that this permission is expected for this type of plugin.

Shell Command Execution

Runs commands on your machine. Be cautious — only use if you trust this plugin.

How to Install

Add this to your MCP configuration file:

{
  "mcpServers": {
    "io-github-terry-li-hm-vivesca": {
      "args": [
        "vivesca"
      ],
      "command": "uvx"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

vivesca

An information metabolism engine. Every text fragment loaded into an LLM's context window is energy — tokens consumed, output influenced, budget spent. Vivesca applies continuous selection pressure so that energy is never wasted.

MCP server is one interface. The metabolism is the identity.

Install

uv add vivesca

What it provides

  • 25 tools across 8 domains — messaging, search, calendar, memory, browser, health, metabolism
  • Structured output — every tool returns Pydantic models with outputSchema
  • Metabolism engine — signal collection, fitness computation, variant evolution, promotion gates
  • 12 resources — budget, calendar, search log, memory stats
  • 3 prompts — research, draft message, morning brief

Hypothesis

Should LLM systems manage their own context? Vivesca tests whether they should, and how.

Claim: Every text fragment in an LLM's context is energy under selection pressure. Continuous metabolism — governed by taste, not just metrics — outperforms manual optimization.

Predictions:

  • Frequency-based pruning creates fragile systems (constitutive knowledge looks unused but is load-bearing)
  • Taste-based fitness outperforms pure token efficiency metrics
  • Systems that metabolize all loaded text outperform systems that optimize only some

Status: Hypothesis with one implementation, zero external validation. The signals accumulating now are the first real data.

Philosophy

Tokens are energy. Text is mass. Taste decides how to spend it. The rest is plumbing.

Read the trilogy:

  1. The Missing Metabolism — tools need evolution
  2. Taste Is the Metabolism — taste is the organizing principle
  3. Everything Is Energy — one equation

vivesca.org

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Links

Source CodePyPI Package

Details

Published March 21, 2026
Version 0.2.2
0 installs
Local Plugin

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