Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Trazum as an MCP server: let an agent price and budget its own prompts before it sends them.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"trazum": {
"command": "npx",
"args": [
"-y",
"@trazum/mcp"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add trazum -- npx -y @trazum/mcpIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"trazum": {
"command": "npx",
"args": [
"-y",
"@trazum/mcp"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"trazum": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@trazum/mcp"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto Davmunrey bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (2.7.7) kam gestern in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, topo^alpin
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
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.
Avalanche bulletins and mountain weather forecasts for any place in the Alps.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
Find where your AI usage costs money, choose a change, and check the result. Trazum analyses local usage logs and prompts, ranks opportunities such as caching and model changes, and keeps estimates separate from measured outcomes.
Open source · Local analysis · No provider key needed to get started
Requires Node.js 20 or newer. npx may download Trazum from npm.
npx @trazum/cli bill
*Illustrative data from examples/claude-projects, not a customer result. Generated from the CLI output.*
With no path, bill reads the local sessions of Claude Code, Codex and Gemini CLI, names each folder it reads, and splits the result by agent, project and model, with each session's subagents and workflows under the project they ran for; --by day|week|month adds the period you ask for. On a subscription, this is API-equivalent cost, not what you paid. Unpriced models are reported as gaps. Local analysis does not upload your files.
Have a supported usage export instead? Pass its path:
npx @trazum/cli bill ./usage-export.jsonl
Supported inputs · Try sample data in your browser
For teams paying for API usage, the useful question is what to change next. Start with your largest workload, review the assumptions behind one finding, and evaluate quality before changing models or prompts.
bill shows the recorded cost and coverage gaps.plan ranks opportunities from a normalized usage log.verify compares the saved plan with later usage, including cases where the evidence cannot settle the result.Follow the first-report-to-verification walkthrough. A projected saving is not a guaranteed reduction in your invoice.
A smaller API-equivalent estimate does not reduce a fixed subscription fee. Use Trazum to inspect conversation growth, review redundant prompt text and set token budgets for instructions you control. Check task quality before keeping a shorter prompt. This does not automatically manage your agent's context or guarantee more messages under your provider's limits.
Subscription efficiency workflow.
In the [Tasks dashboard](https://trazum.vercel.app/?tab=tasks) and CLI/MCP 2.6.0: task efficiency connects Claude Code/Codex task usage, repeated-tool evidence, a reversible instruction policy and an explicit acceptance decision. Compare observed usage before and after a change without inferring success or guaranteed savings.
npx @trazum/cli bill ./usage-export.jsonl --html-out bill.html
PDF, CSV and Markdown exports are also available. Review the report before sharing it: it contains usage and cost information.
Claude Code is the first native integration, not a provider lock-in. Codex session imports, normalized usage logs and provider exports feed the same core. MCP clients can query Trazum without having a native transcript adapter.
| You need | Start here |
|---|---|
| A terminal report | Quick start |
| Native agent session import | Claude Code or Codex |
| A task-level efficiency experiment | Analyze, apply a policy and compare, since 2.6.0 |
| An agent integration | CLI, MCP and skill workflows |
| An API contract or enforced call path | Local HTTP API or gateway |
| The full documentation | Task-based index |
Harness, model and payment mode are separate facts. An API-equivalent estimate is not a subscription invoice; a model without a price remains a gap.
Explore advanced workflows, commands, architecture and limitations
One agent costs what it costs. A fleet of them spends in a loop nobody is watching per iteration, and the bill arrives a month later as one number with no per-decision detail inside it.
Trazum installs into that loop. The MCP server's first tool is spend_guard, and it is the only one here whose trigger is not a sentence somebody types:
"May I spend this?" -> yes, no, or cannot-tell.
A refusal carries the cheaper ways to make the same call, each priced for that call and each naming what it assumes. The ceilings come from your trazum.config.json; the spend so far comes from the usage log your host already writes. Nothing is called and nothing is spent to answer.
claude plugin marketplace add Davmunrey/Trazum
claude plugin install trazum@trazum
That one line brings the skill and the MCP server. An agent that reads Agent Skills from the repository instead gets the same skill with npx skills add Davmunrey/Trazum. Every other MCP client reads the same mcpServers JSON, so Cursor (.cursor/mcp.json), Windsurf, Claude Desktop and the rest are one paste:
{ "mcpServers": { "trazum": { "command": "npx", "args": ["-y", "@trazum/mcp"] } } }
The server is listed on the official MCP registry as io.github.Davmunrey/trazum, and every release updates the listing.
[Or run it right now, without installing anything: the Playground](https://trazum.vercel.app/?tab=playground)
That link opens the CLI's pure subset running in the page, against sample files already loaded, through the same @trazum/core functions the terminal runs. Nothing you paste leaves your browser.
*Real output, transcribed. Read the last two lines: the rules recovered $24.00 a month, and the advisory above them is worth $528.40, 22 times more. That gap is the entire argument for this tool.*
*Generated by npm run draw:architecture, not drawn. architecture-image.test.js fails the build if a package exists that the picture does not show, if the core takes a dependency while the picture says it has none, or if a third module is allowed to reach a network without the picture saying so.*
The prompt is the part everyone looks at, and usually the cheap part. In the run above, forty percent of the text came out and it moved 3.5% of the bill. What moved the rest was a question nobody was asking: does this task need the model it is running on?
Every figure has a receipt. Sixteen advisories, each priced per month and reproducible on a single file: caching you are not getting, work that could go through the Batch API, a schema costing tokens on every call to describe a shape the request could carry as a parameter. Underneath them, twelve deterministic rules that shorten the text itself: same input, same output, free, offline, and never touching code, URLs, email addresses or placeholders. On top, an optional LLM pass for the compression rules cannot do, through whichever provider you configure, which never runs unless you ask.
┌──────────────┐
│ @trazum/core │ the library: rules, tokens, pricing └──────┬───────┘ zero dependencies, browser-safe ┌────────────┬─────────────┼─────────────┬─────────────┐ @trazum/cli @trazum/mcp trazum-vscode @trazum/web action/ 55 commands MCP server the editor Next.js comments on for your agents status bar pull requests
@trazum/tokenizer-openai optional: exact counts for OpenAI install it or do not, nothing else changes
| I want to… | Go to |
|---|---|
| Get a first result | Quick start |
| Understand recorded spend | Usage inputs and bill/profile |
| Set budgets | CI gates or gateway decisions |
| Integrate Trazum | CLI, web, library and agents |
| Find a command or a data contract | Command reference and documentation index |
Limitations · Privacy · Pricing · Contributing
The analyser reports sixteen findings, with assumptions attached to each estimate.
1. Tells you where the money actually is. This is the part worth reading first, because it is where the numbers are. Every advisory is priced per month against your own call volume, and none of them is about making the text shorter:
| Advisory | Why it matters |
|---|---|
| Prompt caching | Reading from cache costs 10% of input. The saving is computed over the real stable prefix: in a template with {{placeholders}}, only what precedes the first one is cached — not the whole prompt. |
| Reorder the template | Stable instructions sitting *after* the first variable placeholder never cache today. Trazum prices moving them in front — and with --reorder, does it. |
| Batch API | 50% off input and output when the work tolerates latency. |
| Cheaper model | Complexity heuristic: if the task looks simple, what dropping a tier would save. |
| Output-dominated cost | If you pay more for the answer than for the prompt, shortening the prompt has a ceiling. |
| Promotional pricing | Warns when you are budgeting with an introductory price that expires. |
| Context window | If the prompt does not fit, the call is going to fail. |
| Contradictory instructions | "Answer in English" three paragraphs above "reply in the customer's own language". The model has to pick one, and which one can change between calls — a correctness problem that also costs tokens twice. |
| Redundant examples | Few-shot examples that are near-copies of an earlier one, and what they cost per month. |
| Output format stated twice | A schema shown in a code block and then walked again in prose. The block is the version worth keeping.
Nur der Anfang wird gezeigt; den Rest findest du im Repo