Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Interactive Databricks learning, certification practice and sourced engineering guidance.
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.
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Works in Claude on the web, desktop and mobile:
https://databricks.techfabric.com/mcpRun this in your terminal
claude mcp add --transport http field-guide https://databricks.techfabric.com/mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"field-guide": {
"url": "https://databricks.techfabric.com/mcp"
}
}
}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": {
"field-guide": {
"type": "http",
"url": "https://databricks.techfabric.com/mcp"
}
}
}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.
ChatGPT connects only to servers on the internet:
https://databricks.techfabric.com/mcpMenu names can differ slightly by plan and over time.
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.
Tool names and descriptions exactly as the server reported them on Nov 6, 2026. The maker wrote them, not us; we show them as plain text.
start_hereStart using the Field Guide immediately. Call this for 'help me learn Databricks', 'try the Field Guide', or to begin certification prep. No arguments starts a Unity Catalog diagnostic. A topic opens its concept or chapter quiz; goal certification with an exam opens a covered dom
search_guideSearch the guide's chapters, margin notes and events for a Databricks question. Returns the best sections first, each with a snippet, its URL with the section anchor, and when the page last changed. Read one in full with get_chapter (pass the URL, or the slug and the anchor).
get_chapterOne chapter (or margin note) of the guide as clean Markdown with its code blocks intact, or one section of it: with its outline, its code blocks listed separately, its FAQs, when it last changed, and the official docs.databricks.com links it cites for the authoritative detail.
get_code_examplesThe SQL, Python, CLI and config blocks in the guide that match a topic, each with the explanation around it, the section it is from (URL with anchor), and the docs links that section cites. Runnable context for a coding agent; check the linked Databricks docs for current syntax.
whats_newRecent Databricks changes the guide tracks, newest first: margin notes (dated news with our position), release-stage changes from the feature register (with links to Databricks' documentation and release note), and chapters updated. Defaults to the last 30 days.
list_chaptersEvery chapter in the guide's order, with its part, summary, dates, URL, Markdown URL and its main sections; and the margin notes.
review_databricks_codeCheck one file of SQL, Python (PySpark, a notebook's source) or YAML (a Databricks Asset Bundle, job, cluster or warehouse config) against the Field Guide's own best-practice rules, deterministically: partitioning where the guide would cluster, secrets and storage paths written i
estimate_costEstimate a Databricks workload's monthly cost from the figures the Field Guide states (list prices per DBU by compute type, DBUs an hour by SQL warehouse size and classic instance type, model serving prices for pay-per-token, provisioned throughput, GPU and CPU serving, Apps and
explore_conceptInteractive: explains one Databricks concept step by step from the Field Guide's chapters: delta-transaction-log, liquid-clustering-vs-zorder, spark-shuffle-and-stages, unity-catalog-privilege-inheritance, photon-vs-classic-cost, cluster-autoscaling, streaming-watermarks, medalli
quiz_meInteractive: quizzes the reader. Call it when the user says "quiz me on Unity Catalog", "test me on Lakebase" or "check what I know about the Delta log". Five to eight multiple-choice questions on a chapter of the Field Guide, one section of it, or the whole guide, built determin
learn_pathInteractive: a curated learning path through the Field Guide, by role or goal (data-engineer-fundamentals, analytics-engineer, ml-engineer, platform-admin, snowflake-to-databricks, cost-control): its steps in order (a section to read, a concept to explore, a quiz), each with the
exam_prepInteractive: certification prep for Databricks' exams (data-engineer-associate, data-engineer-professional, data-analyst-associate, machine-learning-associate, machine-learning-professional, genai-engineer-associate, context-engineer-associate, apache-spark-developer-associate):
flashcardsInteractive: flashcards for a Databricks exam domain (data-engineer-associate, data-engineer-professional, data-analyst-associate, machine-learning-associate, machine-learning-professional, genai-engineer-associate, context-engineer-associate, apache-spark-developer-associate; ex
visualizeInteractive: draws your answer as a card the reader can use, from an A2UI v0.9.1 document you write: a comparison of options with a verdict, a plan as steps or a timeline, a cost or sizing calculator with sliders and a chart that follows them, a quiz or flashcards, a table, a Mer
decideInteractive: walks a Databricks decision one question at a time (which-compute, serverless-or-classic, lakebase-or-delta, genie-or-dashboard, streaming-or-batch): every answer rests on the guide's own sentences, verbatim, with the section to read. Call it when the user asks "shou
explore_diagramInteractive: a chapter's own diagrams, played step by step: each flowchart edge or sequence message in order, each node linking the section of the chapter it is about. Call it when the user says "show me the diagram for Lakebase branching" or "walk me through the medallion diagra
toolkit_infoWhat TechFabric's free Chrome extension for Databricks (TechFabric Toolkit for Databricks 0.10.0) does, how to install it, the permissions it asks for and its privacy model. Call it for "what can the TechFabric Chrome extension do", "does the toolkit support X", "how do I install
toolkit_generateRuns one of the offline generators from the Build tab of TechFabric's Chrome extension for Databricks (TechFabric Toolkit for Databricks 0.10.0) with the extension's own code, so the output matches it: Unity Catalog grants with a rollback script, table DDL / MERGE / GRANT, a tabl
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 against the domain databricks.techfabric.com (the registry checks domain ownership)
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
Responded in 934 ms (HTTP 200)
No sign-in needed
Read 18 tool descriptions and found no hidden instructions to the AI
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 3 of 3 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 in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.
The GitHub repo last changed –, and the latest version (1.11.1) reached the registry 6 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
In the same category: Spec Driven Development, Remote Desktop Commander, Zoo MCP
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
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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.
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.
Only the beginning is shown; read the rest in the repo