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
Flameox
Overview
Description from the maker (original English)
Bounded local runtime evidence from explicit artifacts and typed direct targets.
PopNx MCP’s three pillars
These three are never merged into one score: opinions, measurements and popularity are different things.
- User voiceiNo reviews yetReviews open together with accounts in a later step
- Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
- UsageiNot measured yet★ –
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.
You need
- PyPIPython’s uv installed (for the uvx command)
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"flameox": {
"command": "uvx",
"args": [
"flameox",
"mcp",
"serve"
]
}
}
}Run this in your terminal
claude mcp add flameox -- uvx flameox mcp serveOr copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"flameox": {
"command": "uvx",
"args": [
"flameox",
"mcp",
"serve"
]
}
}
}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.
Or copy the settings yourself
Paste into .vscode/mcp.json in your project
{
"servers": {
"flameox": {
"type": "stdio",
"command": "uvx",
"args": [
"flameox",
"mcp",
"serve"
]
}
}
}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 morluto, 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 32509 servers in this category
- Published to the registry more recently than 59% of the other 32509 servers in this category
- Basic checks equal to or better than 100% of the other 32509 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 Flameox 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 (0.2.9) reached the registry 27 days ago.
Which apps can use it?
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
What can I use instead?
In the same category: Spec Driven Development, Remote Desktop Commander, Fomu MCP
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
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
Fomu MCP
by gabrielmahia
Kenya government form guides: checklists, draft letters, eCitizen, Huduma, timelines. Sample data.
Runs on your computerUpdated today
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.
flameox
Bounded local runtime evidence for coding agents.
Flameox coordinates profilers, benchmark tools, trace processors, and direct local targets. It turns an explicit artifact or command into bounded evidence while keeping durable preservation optional. The agent chooses hypotheses and experiments; Flameox records observed inputs, execution provenance, typed evidence, coverage, and limitations.
There is no workspace to initialize or project configuration to maintain. Pass exact artifact paths to analysis and an explicit argv plus absolute working directory to capture. Flameox does not search parent directories, edit project files, or provide a hosted service.
Quick start
Configure an MCP client with the global setup command:
npx flameox@latest setupSetup detects supported clients and asks which configurations to update. For automation, select clients explicitly, for example --client codex --yes or --all --yes; --dry-run reports the paths and actions without writing. Setup preserves unrelated client configuration and does not change project files. See the npm package guide for details.
Update existing MCP registrations with:
npx flameox@latest updateupdate --check reports available updates without changing configuration. Updates preserve each client's provider extras and settings, verify the new environment before changing release pins, and report which clients need a restart or reconnect. Use --client codex to select one client, or --version 0.2.8 to select a specific release, including for rollback. The Python CLI exposes the same flameox update command.
For direct CLI use, pass exact artifact paths or an explicit command:
uvx flameox analyze preview_artifact /absolute/path/to/artifact.jsonuvx flameox capture --provider direct --cwd "$PWD" -- python benchmark.py
To launch the stdio MCP server manually:
uvx flameox mcp serveFor local development, clone the repository, install its development dependencies, and inspect the available tools:
git clone https://github.com/morluto/flameox.gitcd flameox uv sync --extra dev --extra memory --extra trace --extra cpu uv run flameox mcp inspect
Evidence and storage
Analysis and unpreserved capture use bounded session scratch. Session analysis_id values expire when evicted or when the server stops. Explicit preservation creates the user-level Flameox data directory and stores native bytes and a canonical evidence bundle by SHA-256. Set FLAMEOX_DATA_DIR to choose another location. Preservation is optional; it does not imply full console-output retention.
Flameox distinguishes observed, derived, and inferred claims. Profiles guide exploration but do not establish causality or performance improvement. Confirmatory claims require representative workloads, declared metrics and estimands, compatible identities, preserved samples, and a semantic oracle.
MCP
The MCP server has no workspace binding. It exposes named analysis and capture tools through the same operation registry as the CLI. Analysis tools accept explicit sources; capture tools accept a typed target and provider. Tool schemas expose operation-specific fields directly. Inspect the catalog with flameox mcp inspect; use --tool TOOL_NAME for focused schemas and examples. The complete contract and current tool catalog are in the interface guide.
Tools return their full bounded results inline, including failures and recovery actions. Preserved evidence has a durable evidence_id; inspect_evidence returns its redacted metadata and replay sources inline.
Capture takes argv, not a shell string. A direct target supplies an absolute working directory and bounded environment overrides. Results may include next_page; replay its named analysis tool and arguments unchanged. Capture continuations read collected artifacts and do not rerun the target. MCP work belongs to the live request, so cancellation applies directly and no detached job survives a restart.
Documentation
- Architecture describes process and package boundaries.
- Storage and evidence defines preservation and provenance.
- Investigations covers experiments, comparison, and evidence quality.
- Adapters documents provider compatibility and integration policy.
- Runtime safety covers limits, recovery, integrity, and privacy.
- Interfaces defines CLI and MCP contracts.
- Testing describes test selections and known proof gaps.
Development
Flameox requires Python 3.12 or newer and uses the committed uv.lock. See CONTRIBUTING.md for development setup and contribution guidance.
uv run ruff check src tests toolsuv run ruff format --check src tests tools uv run mypy src tests tools uv run pytest -q
Flameox is licensed under the MIT License.