Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
7 MCP servers for 1,084 tokens instead of 20,005. An MCP router that loads tool schemas on demand.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"tool-guardian": {
"command": "uvx",
"args": [
"tool-guardian"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add tool-guardian -- uvx tool-guardian프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"tool-guardian": {
"command": "uvx",
"args": [
"tool-guardian"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"tool-guardian": {
"type": "stdio",
"command": "uvx",
"args": [
"tool-guardian"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 LuminariSoftwares 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.10.0)은 그저께 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, ScienceShot science reference
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Sourced, citable answers in radiation and particle physics, photonics, electronics and quantum.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Tool Guardian
Status: active development -- changelog
mcp-name: io.github.LuminariSoftwares/tool-guardian
Seven MCP servers for 1,084 tokens instead of 20,005.
One MCP server in front of all your others, so the model fetches a tool schema only when it needs one.
Nothing to install: uvx runs it from PyPI. The example server below is the MCP filesystem server, which runs with npx, so that one line needs Node.js — the router itself is Python 3.9+ and standard library only.
uvx tool-guardian --version
uvx --from tool-guardian tool-guardian-setup add files -- npx -y @modelcontextprotocol/server-filesystem "$HOME" uvx tool-guardian --selftest claude mcp add --scope user tool-guardian -- uvx tool-guardian # or any client: see "Run" below
Or tell your coding agent: Install tool-guardian (docs: https://raw.githubusercontent.com/LuminariSoftwares/tool-guardian/main/llms.txt) and route my MCP servers through it.
Prefer it installed? pip install tool-guardian, then drop the uvx prefixes (tool-guardian-setup add ..., tool-guardian --selftest).
Success looks like added 'files' to ~/.tool-guardian/mcp.json, then from --selftest 1 backend(s) up, 14 tools reachable. and a router tools cost ~N tokens vs ~M line. Already have servers in Claude Desktop, Cursor or Windsurf? tool-guardian-setup import copies them instead of add. In the client, ask for something one of your servers does; the model should call list_capabilities (or search_capabilities) and then call_tool.
A real session against two servers (files and git), abridged only where marked. The model asks for the catalogue, narrows to one server, checks one tool's arguments, then calls it:
> list_capabilities()
[files] 14 tools: read_file, read_text_file, read_media_file, read_multiple_files, write_file, edit_file, create_directory, list_directory, list_directory_with_sizes, directory_tree, move_file, search_files, get_file_info, list_allowed_directories [git] 12 tools: git_status, git_diff_unstaged, git_diff_staged, git_diff, git_commit, git_add, git_reset, git_log, git_create_branch, git_checkout, git_show, git_branch
NEXT STEP: use search_capabilities with a keyword (or list_capabilities with one server name) to see a tool's args, then call_tool.
list_capabilities(server="files")
files.read_file: Read the complete contents of a file as text. DEPRECATED: Use read_text_file... args: path:string, ?tail:number, ?head:number files.read_text_file: Read the complete contents of a file from the file system as... args: path:string, ?tail:number, ?head:number ... 11 more tools ... files.list_allowed_directories: Returns the list of directories that this server is allowed to access.... args: (no arguments)
NEXT STEP: you have not answered the user yet. Pick the tool above that does the job and use call_tool with server files, that tool's name, and the args listed under it.
describe_tool(server="files", tool="read_text_file")
files.read_text_file: Read the complete contents of a file from the file system as... required args: path:string
NEXT STEP: use call_tool with server files, tool read_text_file, args: path:string, ?tail:number, ?head:number.
call_tool(server="files", tool="read_text_file", args={"path": "project/README.txt"})
hello from tool-guardian
NEXT STEP: answer the user from this result.
Only the router's own six tools were in the model's context the whole time; the 26 backend tools were never sent.
The result line is this repo's bench, run against the recorded tools/list answers of seven public MCP servers (no network, no model; abridged where marked):
$ python bench/bench_tokens.py
Token counting method: estimate:chars/3.5
| server | tools | tokens (full schemas) | ... | Total | 95 | 20005 |
Every request: 20005 tokens of tool schemas without tool-guardian, 1084 with it (94.6% less).
<!-- c1 --><!-- c2 -->
Run 2026-11-05 on the v0.10.0 tag. Test suite (pip install -r requirements-dev.txt && python -m pytest -q), run 2026-11-05:
428 passed, 4 skipped in 85.82s (0:01:25)
--selftest proves the *saving* and that your backends start — it does not prove your model will drive the router in your harness. See Model requirement.
One MCP server in front of all your others. Tested with Claude Code, OpenCode, Cline and Continue (one scripted-model turn per client, see Works with ); Claude Desktop, Cursor and other stdio MCP clients: expected, not yet tested.
Quick start · Works with · DeepSeek Harness · Install both · First 5 minutes · Why · Two ways to run it · Architecture · Install · Measure it · Output ladder · DSH bundle · Compatibility · Changelog
An MCP server that sits in front of your other MCP servers and exposes 6 router tools (8 with skills) instead of dozens of specific ones: four generic ones to list, search, describe and call the tools behind it, plus two for tool-group costs and archived results (see Tools) — discovering the rest on demand — so tool definitions stop eating your context window before the model reads a word.
The router never talks to the model backend, so it does not matter whether Ollama, LM Studio, vLLM or llama.cpp serves your model; what matters is that your client's model calls tools (run with Ollama; the others expected, not yet tested).
Companion to Context Guardian: Context Guardian compacts the conversation before the window fills; Tool Guardian keeps the tools from filling it in the first place. Two halves of the same problem.
| Without Tool Guardian | With it | |
|---|---|---|
| 7 MCP servers on a 32K model (bench) | 20,005 tokens of schemas on every request (61 % of the window) | 1,084 tokens (3 %); a schema is fetched only when the model asks |
| A 3,000-line build log with one error (bench) | 115,945 characters land in the conversation | 4,540 characters, the full original archived and one call away |
| A backend that fails to start | an empty tool list the model silently works around | status UNKNOWN plus the real error (e.g. could not start: …), never an empty list |
It is the wrong tool in two cases, and saying so is cheaper than finding out:
tools/list; one small server behind it is close to break-even (--selftest prints the real arithmetic for *your* servers before you commit to it). The saving grows with every server added and is largest where it matters most — a 32K local model with half a dozen servers.It also does not help if your model will not call tools reliably in the first place: see Model requirement.
pip install tool-guardian, then one entry in your client. Every example below starts the same command, tool-guardian, which reads ~/.tool-guardian/mcp.json: tool-guardian-setup import fills it from the servers you already use.
| Client | Example | Where it goes | Tested |
|---|---|---|---|
| Claude Code | project.mcp.json, hook: settings.json, notes | claude mcp add --scope user tool-guardian -- uvx tool-guardian, or copy to .mcp.json in a project (Claude Code asks once to approve a project server — that file is the client's config, not the router's) ; the hook goes in ~/.claude/settings.json or .claude/settings.json | 2.1.296: full turn; hook in a live session |
| OpenCode | opencode.json | opencode.json in the project, or ~/.config/opencode/opencode.json | 1.18.35: full turn |
| Cline | cline_mcp_settings.json | VS Code: Cline → MCP Servers → Configure MCP Servers; CLI: ~/.cline/data/settings/cline_mcp_settings.json | CLI 3.0.70: full turn |
| Continue | tool-guardian.yaml | .continue/mcpServers/ in the workspace (IDE), or its mcpServers entry in config.yaml | cn 1.5.47: full turn (entry in config.yaml) |
What "full turn" means. On Linux, 2026-10-10, each client got the example's tool-guardian entry unchanged (Claude Code through claude mcp add-json; OpenCode and Continue with a test model provider added beside it; Cline the file as is) and talked to a scripted model (tests/clients/mock_model.py, no real model, no API key). The client sent tool-guardian's router tools to the model. The model's list_capabilities call went through tool-guardian to a stub MCP server, and the answer came back to the model. tool-guardian's call log recorded the client by name (claude-code, opencode, @cline/core, continue-cli-client). Re-run it: pip install -e . then python tests/clients/run_clients.py. This proves the wiring, not that *your* model will use the router: see Model requirement.
The Claude Code hook in a live session. The hook command from settings.json with --mode deny added (wrapped to
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