Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Code graph context engine with 24 MCP tools. 170+ languages via tree-sitter.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"tempograph": {
"command": "uvx",
"args": [
"tempograph"
]
}
}
}Run this in your terminal
claude mcp add tempograph -- uvx tempographPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"tempograph": {
"command": "uvx",
"args": [
"tempograph"
]
}
}
}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.
Paste into .vscode/mcp.json in your project
{
"servers": {
"tempograph": {
"type": "stdio",
"command": "uvx",
"args": [
"tempograph"
]
}
}
}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.
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These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
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
The registry name was verified with the GitHub account Elmoaid, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
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.
The registry does not list a required key, though some servers ask you to sign in on first use.
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).
The GitHub repo last changed –, and the latest version (0.7.2) reached the registry 7 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, zanadir
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
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.
Find what a repository's CI is missing, and which security checks cannot fail the build.
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.
This is the frozen April-2026 Python line (PyPI
tempograph 0.7.4). The live engine is the all-Rusttempograph_rsinElmoaid/outpm(ruling D-1, 2026-08). The benchmark headline below (+18.6%, p=0.049) was re-analysed as p=0.055, not significant (ruling D-7); it is kept as the published record, not as a current claim. Banner added 2026-09-02.
Your AI agent finds the right files. Every time.
TempoGraph builds a dependency graph of your codebase and gives your AI coding agent exactly the files it needs before making changes. One tool call. No guessing.
AI coding agents guess which files to look at. They search by filename, grep for keywords, and hope for the best. In large codebases, they miss critical dependencies, break things downstream, and waste tokens reading irrelevant code.
pip install tempograph
Add to your MCP config (Claude Code, Cursor, Windsurf, or any MCP client):
{
"mcpServers": { "tempograph": { "command": "tempograph-server", "args": [] } } }
Your agent calls prepare_context with a task description. TempoGraph returns the exact files that matter — based on real dependency analysis, not text matching.
Tested on real PRs from django, flask, httpx, fastapi, requests, and pydantic. Task: predict which files need to change.
| Model | Without TempoGraph | With TempoGraph | Improvement |
|---|---|---|---|
| GPT-4o | 21.7% F1 | 27.5% F1 | +27% |
| GPT-4o-mini | 19.2% F1 | 24.5% F1 | +28% |
| qwen2.5-coder:32b | — | — | +18.6% (p=0.049) |
Consistent improvement across every model. 2-3x more tasks helped than hurt. No other code context tool publishes retrieval benchmarks with statistical significance.
your repo ──→ tree-sitter parse ──→ symbols + edges ──→ SQLite graph
│ AI agent calls prepare_context ─────────┘ │ ◄── KEY FILES + callers + callees + risk signals
Beyond prepare_context, TempoGraph exposes 24 MCP tools for deeper analysis when your agent needs it:
| Tool | When to use it |
|---|---|
blast_radius | "What breaks if I change this file?" |
focus | "Show me everything related to auth" |
hotspots | "Which files are riskiest to change?" |
dead_code | "What can I safely delete?" |
diff_context | "What's the impact of my current changes?" |
overview | "Orient me in this new codebase" |
All 24 tools
| Tool | What it does |
|---|---|
prepare_context | One-shot context for a task — the primary tool |
overview | Repository orientation: size, languages, entry points |
focus | Connected subgraph around a symbol — callers, callees |
blast_radius | What breaks if you change this file or symbol |
diff_context | Impact analysis of changed files |
hotspots | Ranked risk list — complexity x coupling x size |
dead_code | Unreferenced symbols — cleanup candidates |
lookup | "Where is X?", "What calls X?" |
dependencies | Circular imports, dependency layers |
architecture | Module-level dependency view |
symbols | Full symbol inventory |
file_map | File tree with top symbols per file |
search_semantic | Hybrid keyword + vector + structural search |
cochange_context | Files that historically change together |
suggest_next | Predicts the next useful tool call |
run_kit | Composable multi-tool workflows |
stats | Token budget estimates |
get_patterns | Codebase conventions and idioms |
report_feedback | Log whether output was useful |
learn_recommendation | Suggestions from feedback history |
index_repo | Build or rebuild the graph |
watch_repo / unwatch_repo | Live incremental updates |
embed_repo | Generate vector embeddings |
# Orient in a new repo
tempograph ./my-project --mode overview
tempograph ./my-project --mode focus --query "authentication"
tempograph ./my-project --mode blast --file src/lib/db.ts
tempograph ./my-project --mode dead
from tempograph import build_graph
graph = build_graph("./my-project") results = graph.search_symbols("handleLogin") importers = graph.importers_of("src/lib/db.ts") dead = graph.find_dead_code()
Python, TypeScript, JavaScript, Rust, Go, Java, C#, and Ruby get deep extraction (custom tree-sitter handlers). 170+ additional languages are supported via generic handler. pip install tempograph[full] for everything.
If TempoGraph saves you time, consider sponsoring the project. Sponsors get early access to new features.
TempoGraph is AGPL-3.0 — free to use, modify, and distribute. If you use TempoGraph in a network service (SaaS, hosted IDE, AI coding platform), AGPL requires you to open-source your service code. If that doesn't work for you, commercial licenses are available.
Contact eali@needspec.com for commercial licensing terms.
AGPL-3.0 — free to use. Network service use requires source disclosure, or a commercial license.