Daimonos
What it does
Agent-optimized MCP server with structured JSON tools. 20-45% token savings.
- Connects 在你的电脑上运行
- Account or key No key needed
- Category 开发者工具
安装
选择你使用的 AI 应用,然后复制设置。
通过 3/3 项检查 · 在你的电脑上运行
第一步:你用哪个 AI?
选择你用的应用,步骤会显示在下方。
可连接 Claude,但需要先准备
不需要密钥,不用安装程序 · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用
双击文件,然后在电脑版 Claude 应用中点击 Install
试一试
用 Daimonos 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude 说正在使用 Daimonos,或回答中出现 Daimonos 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
ChatGPT 暂时无法连接 Daimonos
Daimonos 需要安装在你的电脑上,而 ChatGPT 只能连接在网上运行的服务器
你可以改用这些方式
A · 使用能连接 Daimonos 的应用
- 不需要密钥,不用安装程序 · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用
B · 开发者工具 类中能连接 ChatGPT 的其他服务器
从同类中使用较多的里挑选,仅限用地址即可连接、无需密钥的
- Sentry✓ ChatGPT
- Compiler Explorer✓ ChatGPT
- GitDiagram✓ ChatGPT
Claude Code 暂时无法连接 Daimonos
开发者只提供了电脑版 Claude 应用的安装文件
你可以改用这些方式
A · 使用能连接 Daimonos 的应用
- 不需要密钥,不用安装程序 · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用
Cursor 暂时无法连接 Daimonos
开发者只提供了电脑版 Claude 应用的安装文件
你可以改用这些方式
A · 使用能连接 Daimonos 的应用
- 不需要密钥,不用安装程序 · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用
VS Code 暂时无法连接 Daimonos
开发者只提供了电脑版 Claude 应用的安装文件
你可以改用这些方式
A · 使用能连接 Daimonos 的应用
- 不需要密钥,不用安装程序 · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用
一览
哪些应用可以使用它
依据这个服务器的连接方式和各应用自己的文档,检查于 2026年11月10日。
在你的电脑上运行,适用于
ClaudeGooseLM StudioMsty StudioCherry StudioVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
它能做什么
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
基础检查i
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月13日
- ✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 beardfaceguy 验证,该账户拥有此仓库
- ✓ 通过
仍在维护
代码最后更新于今天
- ✓ 通过
有许可证
使用 MIT
- – 不适用
端点有响应
它在你的电脑上运行,没有互联网端点
- – 不适用
使用 OAuth 登录
在你的电脑上运行,改用本地设置
- … 尚未检查
工具描述中没有隐藏指令
它在你的电脑上运行;我们只能读取互联网端点的工具列表
讨论
提问、分享技巧或报告无法使用。按“有帮助”数量排序。
用户评价
还没有评价
与“开发者工具”中的其他服务器比较i
- 星标数多于此分类中其他 5851 个服务器的 81%
- 发布到注册中心的时间比此分类中其他 5851 个服务器的 53% 更新
- 基础检查结果等于或优于此分类中其他 5851 个服务器的 100%
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
常见问题
Daimonos 安全吗?
它在 3 项适用的基础检查中通过了 3 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
它需要哪些密钥或代码?
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在我的电脑上运行还是在云端?
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
它还在维护吗?
GitHub 仓库最后更新于今天,最新版本(0.1.5)于25天前进入注册中心。
哪些应用可以使用它?
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 MCPB。
有什么可以替代它?
同一分类中有:REA, GitHub, Serena MCP: the IDE for your agent
同类别的其他选择
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
Serena MCP: the IDE for your agent
A powerful toolkit for coding, providing semantic retrieval and editing capabilities.
作者的 README
打开 README
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
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
- Native tool plugins —
git,cargo,gh, anddockerare exposed as first-class MCP tools with structured JSON output. When agents callexec("cargo test"), Daimonos intercepts it and routes through the native plugin instead.
- 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.
- 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%.
- 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):
| 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.
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:
| Instance | daimonos tokens (LLM calls) | mini-swe-agent tokens (LLM calls) | cursor-agent tokens |
|---|---|---|---|
| django__django-11815 | 54,755 (4) | 38,305 (9) | 113,242 |
| django__django-12155 | 53,773 (4) | 33,095 (9) | 348,425 |
| django__django-12708 | 88,765 (6) | 196,492 (22) | 451,349 |
| sphinx-doc__sphinx-8035 | 172,729 (10) | 342,108 (30) | 930,495 |
| sphinx-doc__sphinx-9367 | 66,812 (5) | 18,611 (6) | 230,223 |
| Total tokens | 436,834 | 628,611 | 2,073,734 |
| Total wall time | 84 s | 247 s | 279 s |
| Resolved | 5/5 | 5/5 | 5/5 |
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)
| 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 filtering, bounded capture, and owned teardown |
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 |
git_read | resolve, show_file, list_tree, grep, log, show_commit, diff, blame, refs, ancestry, worktree_status | git with --no-lazy-fetch support |
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 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
0600files under a private0700directory, 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