Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Interactive Databricks learning, certification practice and sourced engineering guidance.
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.
Funktioniert in Claude im Web, auf dem Desktop und auf dem Handy:
https://databricks.techfabric.com/mcpFühre das in deinem Terminal aus
claude mcp add --transport http field-guide https://databricks.techfabric.com/mcpIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"field-guide": {
"url": "https://databricks.techfabric.com/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": {
"field-guide": {
"type": "http",
"url": "https://databricks.techfabric.com/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.
ChatGPT verbindet sich nur mit Servern im Internet:
https://databricks.techfabric.com/mcpMenünamen können sich je nach Tarif und mit der Zeit leicht unterscheiden.
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.
Die Tool-Liste dieses Servers haben wir noch nicht gelesen; wir prüfen die Endpunkte reihum.
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 über die Domain databricks.techfabric.com bestätigt (die Registry prüft, wem die Domain gehört)
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Noch nicht geprüft; wir prüfen die Endpunkte reihum
Noch nicht geprüft; wir prüfen die Endpunkte reihum
Noch nicht geprüft; wir lesen die Tool-Liste, wenn wir den Endpunkt prüfen
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 in der Cloud des Entwicklers. Du verbindest dich übers Internet, ohne etwas zu installieren, aber was du sendest, läuft über die Server des Entwicklers.
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (1.11.1) kam vor 5 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Er verbindet sich per URL, also funktionieren auch Apps, die Remote-MCP-Server akzeptieren, zum Beispiel ChatGPT im Entwicklermodus.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, Symantec Cloud DLP AIops
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.
Governed Symantec Cloud DLP — 14 MCP tools, read-only with audit.
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.
Learn Databricks, practice for a certification, and answer engineering questions with the Databricks Field Guide. Ask "Help me learn Databricks" to start a diagnostic, or "Help me prepare for Data Engineer Associate" to start domain practice. The assistant uses interactive MCP Apps cards where supported and asks one question at a time in text clients. Answers include the guide's source sections and official documentation links.
https://databricks.techfabric.com/mcp
It's a remote server over Streamable HTTP: no local server to run, no sign-in, and free public learning. The optional Claude Code plugin below bundles the connection and six skills; connecting MCP alone does not install skills.
Ask how to add a Unity Catalog row filter, and the agent gets the guide's section on it, the SQL function from that section and the Databricks documentation behind it. Databricks' own docs stay the authority on syntax and limits, which is why every answer links to them.
This isn't Databricks' own MCP server. Databricks runs managed MCP servers inside a workspace that act on your data. This one is built and run by TechFabric, a Databricks partner, and it never connects to a workspace.
Registry descriptors and an optional client plugin. The official MCP Registry entry names this repository, and GitHub's MCP Registry shows this README in Copilot. The server's code isn't here and isn't open source.
| File | What it is |
|---|---|
server.json | The server's entry in the official MCP Registry, copied as published |
glama.json | Maintainer list for Glama |
icon.png, icon-light.png | The TechFabric mark at 256 px, for dark and light backgrounds |
LICENSE | Apache-2.0, for these files only |
.claude-plugin/marketplace.json | Claude Code marketplace descriptor |
plugins/field-guide/ | Anonymous MCP connection, six skills and a connection-check script |
The live server and the registry are the source of truth. If this README and the server's tools/list ever disagree, the server is right. A weekly GitHub Action compares server.json with the registry and opens a pull request when the entry has changed.
To install both skills and the connection, run in Claude Code:
/plugin marketplace add Fabric-Pro/databricks-field-guide-mcp
/plugin install field-guide@techfabric-field-guide
Start a new session. The skills cover general Databricks questions, guided learning, certifications, code review, cost estimates and recent changes. They complement Databricks' development plugin, not replace workspace access or deployment tooling. Keep one Field Guide connection to avoid duplicate tools.
For just the MCP connection, without skills:
claude mcp add --transport http databricks-field-guide https://databricks.techfabric.com/mcp
Add --scope user to have it in every project.
From a clone of this repository:
agy plugin install ./plugins/field-guide
Start a new session. The native agy manifest and mcp_config.json bundle the same six skills and preserve the HTTP connection without Claude-plugin conversion.
Open Customize, then Connectors, choose Add and then Add custom connector. Name it, paste https://databricks.techfabric.com/mcp, keep the authentication settings Claude detects, and choose Add. On a Team or Enterprise plan, an owner may have to add the connector for the organisation first.
At chatgpt.com/plugins, choose + and then Add custom MCP server. Paste the URL under Connection, choose no authentication, and create it. In a chat, type @ and pick it. If Add custom MCP server isn't there, your workspace's admin has to turn it on.
codex mcp add databricks-field-guide --url https://databricks.techfabric.com/mcp
Or by hand, in ~/.codex/config.toml:
[mcp_servers.databricks-field-guide]
url = "https://databricks.techfabric.com/mcp"
In ~/.cursor/mcp.json for every project, or .cursor/mcp.json for one:
{
"mcpServers": { "databricks-field-guide": { "url": "https://databricks.techfabric.com/mcp" } } }
In .vscode/mcp.json, then start it from that file or the MCP view. The tools show up in Copilot's agent mode.
{
"servers": { "databricks-field-guide": { "type": "http", "url": "https://databricks.techfabric.com/mcp" } } }
In VS Code, use the configuration above. Copilot CLI saves the server to ~/.copilot/mcp-config.json, for every project:
copilot mcp add --transport http databricks-field-guide https://databricks.techfabric.com/mcp
Copilot's coding agent on github.com takes it in the repository's Settings, under Copilot and MCP servers. Every tool is read-only, so it can have all of them:
{
"mcpServers": { "databricks-field-guide": { "type": "http", "url": "https://databricks.techfabric.com/mcp", "tools": ["*"] } } }
Point the client at the URL with the Streamable HTTP transport and no authentication. A client that only speaks stdio can reach it through mcp-remote:
npx mcp-remote https://databricks.techfabric.com/mcp
Gemini CLI and OpenCode each have their own line in the setup guide.
| Tool | What it does |
|---|---|
start_here | Starts a working diagnostic, a named concept lesson or certification practice, with an Apps card and text fallback |
search_guide | Finds the chapter sections, margin notes and events that answer a Databricks question, best first, each with its URL and section anchor |
get_chapter | Reads a chapter, a margin note or one section of either as Markdown, with code, FAQs and the docs.databricks.com links it cites |
get_code_examples | Returns the SQL, Python, CLI and config blocks that match a topic, with the explanation around each one |
whats_new | Lists recent Databricks changes the guide tracks, newest first: margin notes, release-stage changes and updated chapters |
list_chapters | The table of contents, with each chapter's part, summary, dates and main sections |
review_databricks_code | Checks one SQL, Python or YAML file (a bundle, job, cluster or warehouse config) against the guide's own rules. Each finding gives the line, why, the fix, the guide's sentence with its section URL and the docs it cites, and the result lists the sections worth reading |
estimate_cost | Estimates a workload's monthly cost from the figures the guide states, as a range with its assumptions. Every number carries its source sentence, section URL, date and pricing page, and where the guide has no figure it says so instead of guessing |
explore_concept | Opens a guided, interactive concept walkthrough |
quiz_me | Asks sourced questions and scores the reader's actual answers |
learn_path | Provides role-based learning steps and checks progress supplied by the reader |
exam_prep | Maps certification domains to guide coverage and official exam guides |
flashcards | Practices sourced terms by chapter or exam domain |
visualize | Builds a guide-grounded diagram or chart |
decide | Compares engineering choices from the guide's stated trade-offs |
explore_diagram | Opens an interactive walkthrough of a chapter diagram |
toolkit_info | Says what TechFabric's free Chrome extension for Databricks (the TechFabric Toolkit for Databricks) does, feature by feature: where each shows up, whether it needs your connected workspace, and the tool here that does the same; plus install, permissions and privacy |
toolkit_generate | Runs the extension's offline generators with its own code: Unity Catalog grants with rollback, table DDL and MERGE, bundle YAML and CLI, Terraform, Auto Loader, Lakeflow and CDC starters, data-quality checks, cost SQL, an error decoder, a pre-flight check for destructive SQL, MLflow and serving templates, and its snippet libraries |
All eighteen are read-only, and none calls a model: the review and the estimate are deterministic checks against the guide's text, the toolkit's generators run the extension's own code, and your agent does the reasoning. A rule applies only while the guide still says what it cites. The rules leave out what the guide doesn't argue, such as SELECT * or collect() on their own.
Three resources come with them: fieldguide://llms.txt, one line per page; fieldguide://whats-new, the last 30 days of changes as JSON; and fieldguide://page/{+path}, any published page as Markdown. Hosts that render MCP Apps show the results as an interactive view instead of plain text: since 1.3.0 that includes the review's findings and the estimate as a table.
Hosts that support MCP prompts show these as slash commands. In Claude Code they're /mcp__databricks-field-guide__ .
| Prompt | What it does |
|---|---|
start | Starts a first learning or certification session |
learn | Teaches a topic with guide sections and practice |
quiz | Runs a sourced quiz one question at a time |
explain | Opens an interactive concept explanation |
path | Starts a role-based learning path |
exam | Prepares a certification's domain map and practice |
flashcards | Starts a recall deck |
estimate | Estimates a named workload's cost from cited rates |
databricks-review | Reviews this repository's Databricks setup against the guide. Your agent collects the bundles, notebooks, SQL and compute configs, runs review_databricks_code on each and summarises the findings with links |
databricks-cost | Estimates what the repository's workloads cost with estimate_cost, with every figure's source and date and the gaps stated plainly |
whats-new | Summarises what Databricks changed lately and which of it touches this repository |
field-guide-chapter | Puts a chapter, or one section of it, into the conversation as Markdown |
field-guide-code | Finds the guide's code examples for a topic, optionally from one chapter |
Chapter and section arguments complete as you type, and so does the page resource's path. MCP completes prompt arguments, not tool arguments, so these prompts are where get_chapter's chapter names complete.
On MCP 2026-07-28 a client can subscribe with subscriptions/listen to fieldguide://whats-new or any fieldguide://page/.... When a deploy of the guide changes a subscribed resource, such as a new margin note, a rewritten chapter or a feature moving release stage, the server sends notifications/resources/updated. Clients on 2025-11-25 have no stream to push on, so they read whats_new instead.
Every answer says when its page last changed and how long a client may cache it: 10 minutes for what's new, 15 for search and an hour for chapters and code. The index is rebuilt on every deploy of the guide.
Nur der Anfang wird gezeigt; den Rest findest du im Repo