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Daimonos

  • 2 repo stars
  • Updated July 27, 2026
  • beardfaceguy/daimonos

Daimonos is an MCP server that serves agent-optimized structured JSON tools to reduce token use on tool calls.

About

Daimonos is a Model Context Protocol server built for coding agents that need tool results in tight structured JSON instead of chatty prose or oversized blobs. developers running long Claude Code or Cursor sessions install it to shrink repeated context growth; the project cites roughly twenty to forty-five percent token savings when agents lean on its tool shapes. Distribution is via stdio MCPB binaries from GitHub releases, with separate builds for x86_64 and aarch64 on Linux and macOS, each with a published SHA-256 for integrity checking. There is no cloud API key gate in the catalog metadata, which lowers friction for local-only setups. You still need an MCP client that can launch the correct platform binary. For developers measuring burn rate per feature branch, Daimonos is a tactical efficiency layer on top of your existing agent workflow rather than a replacement for domain-specific MCP servers.

  • Structured JSON tool outputs aimed at agent clients
  • Documented 20–45% token savings versus verbose tool payloads
  • stdio MCPB release bundles for Linux and macOS x86_64 and aarch64
  • Version 0.1.4 with pinned fileSha256 per platform artifact
  • No required API keys in published server metadata

Daimonos by the numbers

  • Data as of Jul 28, 2026 (Skillselion catalog sync)
claude mcp add Daimonos -- npx -y beardfaceguy/daimonos

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repo stars2
Last updatedJuly 27, 2026
Repositorybeardfaceguy/daimonos

What it does

Install the Daimonos MCP server so your agent uses compact structured JSON tools and cuts context token burn on every tool round-trip.

Who is it for?

Token-conscious developers who run many tool loops locally on Linux or macOS and want MCPB stdio installs without SaaS keys.

Skip if: Skip if you need hosted remotes only, Windows MCPB support from this catalog entry, or domain APIs like App Store or databases.

What you get

After you wire Daimonos stdio, your agent can consume leaner JSON tool payloads and stretch the same context budget further.

  • Running stdio Daimonos MCP server in your agent config
  • Structured JSON tool surface for agent sessions
  • Platform-selected binary with verifiable release hash

By the numbers

  • Claimed 20–45% token savings
  • Server version 0.1.4
  • Four MCPB platform identifiers in registry metadata
README.md

Daimonos

CI Latest Release License: MIT MCP Registry

An agent-optimized OS layer that makes AI coding agents faster and cheaper.

Daimonos replaces the built-in file, search, exec, and git tools in your AI coding agent with structured equivalents that return compact JSON instead of raw terminal output. The result: fewer tokens consumed, fewer round-trips, and lower API costs — with zero changes to your workflow.

Platforms: Linux (x86_64, aarch64) and macOS (Apple Silicon, Intel). Windows support is planned.

For repository agent/operator conventions, see AGENTS.md (especially Daimonos tool usage policy).

The name comes from Greek daimon (agent/spirit), the etymological root of "daemon."

The problem

When an AI agent runs cargo test, it gets back hundreds of lines of terminal output — progress bars, compile messages, passing test names — when all it needs is "47 passed, 0 failed." The agent pays for every token of that noise: reading it, reasoning about it, and carrying it in context for the rest of the session.

The same waste happens with git status, docker ps, ls -la, and every other shell command. Agents spend 30-50% of their token budget on verbose, unstructured tool output.

How it works

Daimonos runs as an MCP server that your IDE or CLI spawns automatically. It provides the same operations agents already use — read files, write files, search, execute commands, git operations — but returns compact, structured JSON instead of raw text.

Agent: exec("cargo test")

Without Daimonos (raw terminal output):
   Compiling inventory v0.1.0 (/workspace)
    Finished `test` profile [unoptimized + debuginfo] target(s) in 2.31s
     Running unittests src/main.rs (target/debug/deps/inventory-abc123)
running 47 tests
test config::tests::test_default ... ok
test config::tests::test_load ... ok
... (200+ more lines)
test result: ok. 47 passed; 0 failed; 0 ignored

With Daimonos (structured JSON):
{"ok":true,"tests":47,"passed":47,"failed":0,"failures":[]}

Three layers of optimization

  1. Native tool pluginsgit, cargo, gh, and docker are exposed as first-class MCP tools with structured JSON output. When agents call exec("cargo test"), Daimonos intercepts it and routes through the native plugin instead.

  2. Semantic output filters — For commands without native plugins (pytest, make, pip install, eslint, etc.), Daimonos applies semantic compression: test runners return summary + failures only, build commands return "ok" or just the errors, install commands return success/failure.

  3. Protocol-level efficiency — Read deduplication (re-reading an unchanged file returns {"unchanged":true} instead of the full content), compact field names, lazy tool exposure, batch operations, and a terse output directive that cuts LLM prose by ~30%.

Benchmark results

Tested with Claude Opus 4.6 on identical coding tasks (read files, search code, edit, run tests, git operations):

Metric Baseline Daimonos Savings
Output tokens 5,842 3,198 -45.3%
Total tokens 41,239 33,847 -17.9%
Tool calls 17 avg 14 avg -17.6%
Wall time 42.1s avg 35.2s avg -16.4%

Remote benchmarks on AWS (same hardware, same model, same tasks) showed 20.3% cost reduction and 14.0% faster task completion.

60-second demo

Use this script for README readers, release notes, and social posts:

# 1) Install daimonos
cargo build --release
sudo cp target/release/daimonos /usr/local/bin/

# 2) Configure your MCP client (example: Cursor)
# .cursor/mcp.json -> command: daimonos, args: ["--mcp", "-w", "/path/to/project"]

# 3) Ask your agent to run:
# "Run cargo test and summarize failures only."
# "Show git status as structured output."

What to highlight in the demo:

  • same workflows, less tool-output noise
  • structured responses instead of raw terminal spam
  • fewer tokens and fewer round-trips for common coding tasks

Quick start

Install

Pre-built binaries (Linux and macOS):

# Linux x86_64
curl -L https://github.com/beardfaceguy/daimonos/releases/latest/download/daimonos-x86_64-linux.tar.gz | tar xz
sudo mv daimonos /usr/local/bin/

# macOS Apple Silicon
curl -L https://github.com/beardfaceguy/daimonos/releases/latest/download/daimonos-aarch64-macos.tar.gz | tar xz
sudo mv daimonos /usr/local/bin/

From source:

git clone https://github.com/beardfaceguy/daimonos.git
cd daimonos
cargo build --release
sudo cp target/release/daimonos /usr/local/bin/

See docs/install.md for all platforms (ARM Linux, Intel Mac, musl static builds).

Configure your IDE

For most users, start with one of these:

Add Daimonos as an MCP server. For Cursor, add to your project's .cursor/mcp.json:

{
  "mcpServers": {
    "daimonos": {
      "command": "daimonos",
      "args": ["--mcp", "-w", "/path/to/your/project"]
    }
  }
}

That's it. Daimonos starts when your IDE opens the project and exits when you close it. No daemon to manage, no background service.

Setup guides for other tools

What's included

Core tools (always available)

Tool What it does
read_file Read with optional offset/limit, content-hash deduplication
write_file Write with auto-mkdir
edit_file String replacement with diff confirmation
search Regex search (content mode) or file discovery (file mode)
exec Run commands with semantic output filtering
batch Multiple operations in a single round-trip
workspace_info Project type, git status, directory listing, analytics

Native tool plugins (auto-detected)

These appear automatically when the corresponding CLI tool is found on PATH:

Plugin Commands Detected by
git status, log, diff, branch, add, commit, push, pull, checkout .git directory
cargo test, build, check, clippy, fmt, add Cargo.toml
gh pr_view, pr_list, pr_create, pr_diff, pr_checks, api gh on PATH
docker ps, logs, exec, images, inspect, stop, compose_up/down/ps docker on PATH

Additional capabilities

  • Workspace snapshots — Checkpoint before risky edits, rollback on failure
  • Starlark scripting — Bundle multiple tool calls into a single script
  • Token analytics — Per-tool-call tracking with cross-session history (daimonos --stats)
  • Background processes — Start, poll, and kill long-running commands
  • Configurable — All tunables in a single TOML config file

Architecture

Daimonos is a single Rust binary (~15 MB) that speaks MCP (Model Context Protocol) over stdio. Your IDE spawns it as a subprocess — no network, no containers, no setup beyond a JSON config entry.

┌──────────────┐     MCP (JSON-RPC over stdio)     ┌─────────────────┐
│  AI Agent    │ ◄──────────────────────────────► │   Daimonos      │
│  (Cursor,    │                                    │                 │
│   Copilot,   │     Structured JSON responses      │  ┌───────────┐ │
│   Claude,    │ ◄──────────────────────────────── │  │ File ops  │ │
│   etc.)      │                                    │  │ Search    │ │
│              │                                    │  │ Exec      │ │
│              │                                    │  │ Git       │ │
│              │                                    │  │ Cargo     │ │
│              │                                    │  │ Docker    │ │
│              │                                    │  │ GitHub    │ │
│              │                                    │  │ Snapshots │ │
│              │                                    │  │ Analytics │ │
└──────────────┘                                    │  └───────────┘ │
                                                    └─────────────────┘

Under the hood, Daimonos uses an opcode-based protocol where each operation has a numeric identifier and compact field names (c, p, s, n) to minimize token overhead. The MCP layer translates between standard JSON-RPC and the internal opcode format.

Project vision

Daimonos is being built in three phases:

Phase 1: User-space MCP server (current)

A Rust daemon that runs on any Linux or macOS machine and provides agent-optimized tools via MCP. This is what you install today. It proves out the protocol design and structured I/O patterns.

Status: Production-ready. Used daily for real development work. Pre-built binaries available for Linux (x86_64, aarch64, musl) and macOS (Apple Silicon, Intel).

Phase 2: Minimal Linux distro

A purpose-built Buildroot Linux image with Daimonos as the primary user-space application. Designed for cloud deployment where AI agents need a clean, minimal environment. The distro boots in seconds, has no shell or human-facing UI, and runs the Daimonos daemon as PID 1's direct child.

Status: Working prototype. Boots in QEMU, deployable to AWS EC2. Used for remote benchmarking.

Phase 3: Custom microkernel

The long-term vision: a microkernel where Daimonos opcodes become native syscalls. StructFS (a filesystem that stores and returns structured data natively), capability-based security, and a process model designed for agent workloads from the ground up.

Status: Design phase.

Development

Prerequisites

Dependency Required Install
Rust (stable 1.75+) Build rustup.rs
Python 3 + pytest Tests pip install -r tests/requirements.txt

Running tests

# Rust unit tests (350+ tests, parallel-safe)
cargo test

# End-to-end MCP protocol tests (150+ pytest cases)
python3 -m pytest tests/ -v

Running benchmarks

cd benchmarks
./setup-mcp.sh
./run-benchmark.sh baseline   # IDE built-in tools
./run-benchmark.sh daimonos   # routed through daimonos MCP
python3 analyze-results.py results/

See benchmarks/README.md for details.

Configuration

All behavior is tunable via a TOML config file. See docs/configuration.md for the full reference, or daimonos.default.toml for annotated defaults.

Key sections:

  • [index] — Trigram indexer tuning (max depth, file size limits)
  • [search] — Search result limits
  • [process] — Exec timeout, output capping, semantic filters, max concurrent Starlark script threads
  • [pipeline_cache] — Subprocess result cache size, inotify watch cap, extra ignored directories
  • [analytics] — Token tracking (SQLite storage, retention)
  • [tools.*] — Per-tool plugin configuration

Contributing

Daimonos is in active development. If you're interested in contributing, start with the AGENTS.md file for coding conventions, architecture decisions, and the review checklist.

See also:

License

MIT

Recommended MCP Servers

How it compares

Token-efficient generic MCP tooling layer, not a business-operator spec like ChiefLab or an App Store API bridge.

FAQ

Who is Daimonos for?

Daimonos is for developers using MCP-based coding agents who want structured JSON tools and lower context overhead on local stdio setups.

When should I use Daimonos?

Use Daimonos during Build agent-tooling when you are standardizing MCP servers and need leaner tool responses in heavy agent sessions.

How do I add Daimonos to my agent?

Point your MCP client at the matching Daimonos MCPB release binary for your OS and CPU arch over stdio, using the v0.1.4 artifact URLs from the registry.

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