Prototype · Preview: every server in the official registry, synced every 30 minutes. Reviews and accounts come in a later step.
PopNx MCPMCP servers for people who use AI · explained in plain words

Daimonos

by beardfaceguyversion 0.1.5i★ –iRuns on your computer
Registry nameio.github.beardfaceguy/daimonos

Install

Overview

Description from the maker (original English)

Agent-optimized MCP server with structured JSON tools. 20-45% token savings.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Download the maker’s .mcpb file

The link goes to the maker’s own file; we do not host or repackage it. Open the file and Claude Desktop installs it.

Run this in your terminal

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account beardfaceguy, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32433 servers in this category
  • Published to the registry more recently than 67% of the other 32433 servers in this category
  • Basic checks equal to or better than 100% of the other 32433 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Daimonos safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.5) reached the registry 19 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need MCPB on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Symantec Cloud DLP AIops

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Spec Driven Development

by formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago
Install

Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated yesterday
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Daimonos

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.

The single binary also provides ACP, one-shot agent, interactive chat, and socket-daemon runtimes — a full coding-agent harness in its own right; see Agent harness features below and Runtime modes for the explicit subcommands and compatibility aliases.

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":[]}

Four layers of optimization
  1. Native tool plugins — git, 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.
  1. 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.
  1. 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%.
  1. Managed subprocess execution — Command output is bounded while it is read instead of after full buffering. Daimonos owns Unix process groups, retires descendants on cancellation or session shutdown, isolates child environments through an explicit allowlist, and stores background output in private bounded artifacts.

Benchmark results

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

MetricBaselineDaimonosSavings
Output tokens5,8423,198-45.3%
Total tokens41,23933,847-17.9%
Tool calls17 avg14 avg-17.6%
Wall time42.1s avg35.2s avg-16.4%

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

SWE-bench Verified (mini) — three-way harness comparison

Five instances from swe-bench-verified-mini, same model (Claude Opus 4.8) across all three harnesses, each agent running inside the official SWE-bench Docker image for its instance (real test environment), scored with the official swebench evaluation harness:

Instancedaimonos tokens (LLM calls)mini-swe-agent tokens (LLM calls)cursor-agent tokens
django__django-1181554,755 (4)38,305 (9)113,242
django__django-1215553,773 (4)33,095 (9)348,425
django__django-1270888,765 (6)196,492 (22)451,349
sphinx-doc__sphinx-8035172,729 (10)342,108 (30)930,495
sphinx-doc__sphinx-936766,812 (5)18,611 (6)230,223
Total tokens436,834628,6112,073,734
Total wall time84 s247 s279 s
Resolved5/55/55/5

Conclusions:

  • Correctness parity: all three harnesses resolved 5/5 at this sample size, so daimonos's token savings did not cost any resolutions.
  • daimonos was cheapest and fastest: ~30% fewer tokens than mini-swe-agent (the minimal open-source baseline) and ~4.8x fewer than cursor-agent, with ~3x less wall time than either.
  • Caveats: n=5, and run-to-run variance is real (daimonos spent 503k tokens on sphinx-8035 in an earlier identical-config run vs 173k here). cursor-agent's total is mostly cache-read tokens billed at a fraction of input price, so its raw token count overstates its relative cost. Measured API spend for the batch (OpenRouter): daimonos $1.53, mini-swe-agent $1.66; cursor-agent bills via Cursor's backend.

See benchmarks/swebench/ for the runners and methodology.

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:

  • Cursor: Cursor IDE setup
  • Zed: Zed setup
  • Claude Code: Claude Code setup

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
  • Cursor IDE
  • GitHub Copilot (VS Code, Visual Studio, JetBrains, Xcode, Eclipse)
  • Claude Code (CLI + macOS Desktop app)
  • Windsurf
  • Cline (VS Code extension)
  • Gemini CLI
  • Zed Editor
  • Discord integration (bot token, allowlists, read-only tools)
  • Other tools (Claude Desktop, ChatGPT, Continue.dev, BoltAI, etc.)

What's included

Core tools (always available)
ToolWhat it does
read_fileRead with optional offset/limit, content-hash deduplication
write_fileWrite with auto-mkdir
edit_fileString replacement with diff confirmation
searchRegex search (content mode) or file discovery (file mode)
execRun commands with semantic filtering, bounded capture, and owned teardown
batchMultiple operations in a single round-trip
workspace_infoProject type, git status, directory listing, analytics
Native tool plugins (auto-detected)

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

PluginCommandsDetected by
gitstatus, log, diff, branch, add, commit, push, pull, checkout.git directory
git_readresolve, show_file, list_tree, grep, log, show_commit, diff, blame, refs, ancestry, worktree_statusgit with --no-lazy-fetch support
cargotest, build, check, clippy, fmt, addCargo.toml
ghpr_view, pr_list, pr_create, pr_diff, pr_checks, apigh on PATH
dockerps, logs, exec, images, inspect, stop, compose_up/down/psdocker 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 stop long-running commands with admission limits, private bounded logs, and descendant cleanup
  • Configurable — All tunables in a single TOML config file
Managed process lifecycle

Raw exec, background jobs, and CLI plugins (cargo, git, gh, docker, npm, pytest, curl, and shellcheck) share one managed execution layer:

  • Streaming-time bounds — stdout and stderr retain UTF-8-safe head/tail previews without first allocating the complete output
  • Process-group ownership on Unix — cancellation and shutdown send TERM, wait a configurable grace period, then escalate to KILL and reap descendants
  • Secure background artifacts — random exclusive 0600 files under a private 0700 directory, with configurable byte and job-count limits
  • Environment isolation — children inherit only configured parent variables plus explicit session, tool, and per-call overrides; provider and MCP credentials are not ambiently leaked
  • Structured-output integrity — plugins reject truncated JSON rather than reporting an incomplete result as valid

Agent harness features

Beyond the MCP server, the same binary is a complete coding-agent harness: an interactive terminal UI (daimonos agent), an ACP backend for Zed, a one-shot CLI, and a session daemon with attach/detach and remote control.

Many of its recent features come from a systematic study of 60+ open-source agent harnesses (Ai

Only the beginning is shown; read the rest in the repo

Ask PopNx