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Slowplan

by GillMacedoversion 0.1.0i★ –iRuns on your computer
Registry nameio.github.GillMacedo/slowplan

Install

Overview

Description from the maker (original English)

Find why a PostgreSQL query is slow from its EXPLAIN output, without a database connection.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

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: Databases & datasets

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

  • npmNode.js installed (for the npx 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": {
    "slowplan": {
      "command": "npx",
      "args": [
        "-y",
        "slowplan",
        "serve"
      ]
    }
  }
}

Run this in your terminal

claude mcp add slowplan -- npx -y slowplan serve

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "slowplan": {
      "command": "npx",
      "args": [
        "-y",
        "slowplan",
        "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.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "slowplan": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "slowplan",
        "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 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account GillMacedo, 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 Databases & datasetsi

  • More stars than 0% of the other 1146 servers in this category
  • Published to the registry more recently than 82% of the other 1146 servers in this category
  • Basic checks equal to or better than 100% of the other 1146 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 Slowplan 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 (0.1.0) reached the registry 7 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Supabase, MongoDB MCP Server, Elasticsearch MCP Server

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Supabase

Supabase’s official server lets AI create tables, query data and review project settings in your Supabase database.

by supabaseWidely used↓ 235.4K/wk★ 3KUpdated 2 days ago

Computer or cloud✓ supabase.com

MongoDB MCP Server

MongoDB Model Context Protocol Server

by mongodb-jsWidely used↓ 157.1K/wk★ 1.2KUpdated 4 days ago

Runs on your computer

Elasticsearch MCP Server

MCP server for interacting with Elasticsearch

by cr7258Growing↓ 2.7K/wk★ 315Updated 14 months ago

Runs on your computer

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.

slowplan: why is this PostgreSQL query slow?

An MCP server and CLI that reads PostgreSQL `EXPLAIN` output and tells you where the time goes and what to try first. It works from the plan text alone, so it never connects to your database.

A long EXPLAIN ANALYZE is hard to read, and a mistake is easy: Postgres reports per-worker averages under parallel plans, and the slowest-looking node often isn't where the time went. slowplan works out the real time for each step, and ranks problems such as sequential scans throwing away rows, wrong row estimates, sorts and hashes spilling to disk, and nested loops run many times.

What you can ask your agent

  • "This Postgres query is slow. Here's the EXPLAIN ANALYZE output."
  • "Why is the planner doing a sequential scan here?"
  • "I added an index. Did it help?"
  • "What's the first thing to fix in this plan?"

Install

As a Claude Code plugin:

claude plugin marketplace add GillMacedo/slowplan claude plugin install slowplan@slowplan-marketplace

As an MCP server, for any client:

{"mcpServers": {"slowplan": {"command": "npx", "args": ["-y", "slowplan@0.1.0", "serve"]}}}

As a CLI, with Node 18 or newer:

npx slowplan review plan.txt

Or with Go 1.27 or newer: go install github.com/GillMacedo/slowplan@latest.

Usage

Get a plan with EXPLAIN (ANALYZE, BUFFERS) , in text or JSON. `ANALYZE` really runs the query, so wrap anything that writes in a transaction you roll back.

Here's a real plan from PostgreSQL 17, on made-up tables:

$ make demo Execution 48.9 ms, planning 0.3 ms

Where the time goes: 80.8% 39.5 ms Bitmap Heap Scan on orders 3.9% 1.9 ms Bitmap Index Scan on orders_status_idx

HIGH PG102 Bitmap Heap Scan on orders The index doesn't cover the whole filter. Read and threw away 84857 rows to keep 857, using filter (bucket = 7). Try: Candidate to test: CREATE INDEX CONCURRENTLY ON orders (bucket), or add these columns to the index in use.

These are leads from one run. Test a fix on realistic data before relying on it.

To check a change, compare the plans from before and after:

slowplan compare before.txt after.txt

On a real example in examples/, adding the index that slowplan suggested took a query from about 25 ms to 0.1 ms.

Add --json for JSON, or --fail-on high to exit 1 in CI. Use - to read from stdin.

What it finds

RuleFinds
PG101A sequential scan throwing away most of the rows it reads
PG102An index that doesn't cover the whole filter
PG103A join producing rows and then throwing them away
PG104A bitmap recheck throwing away many rows
PG105Row estimates off by 10 times or more
PG106A nested loop's inner side running 1,000 times or more
PG107A sort spilling to disk
PG108A hash table split into batches on disk
PG109Fewer parallel workers than planned
PG110An index-only scan still visiting the table often
PG111A bitmap that became lossy
PG112Reading about 80 MB or more from outside shared buffers
PG113Planning slower than running the query
PG114JIT taking 100 ms or more

Severity comes from the share of the query's time: high is 20% or more, and low is under 5% or under 1 ms. These thresholds are judgment calls.

MCP tools

ToolDoes
postgres_plan_reviewReviews one plan, from text or a file
postgres_plan_compareCompares plans from before and after a change

Limits

  • Suggested indexes are candidates. A plan shows one query with one set of values, and not your other indexes or what an index costs on writes. Test on realistic data.
  • One run isn't a benchmark. A cold cache or a busy server changes timing.
  • It can't see locks, network time, or anything outside the plan. A plan with estimates only has nothing measured, and slowplan says so.
  • Times under parallel plans are estimates, because Postgres reports averages across workers.
  • PostgreSQL only. Text plans from other tools, or heavily edited ones, may not parse. JSON is the most reliable.
  • Plans can hold values from your query. slowplan stays on your machine, but your MCP client sends tool results to its model.

FAQ

How do I read EXPLAIN ANALYZE output? Give it to slowplan, which shows where the time goes.

Why is Postgres doing a sequential scan? Often there's no useful index, or the filter keeps so many rows that an index wouldn't help. PG101 shows how many rows were thrown away.

How do I find out if a sort or hash is using disk? PG107 and PG108 flag them.

How is this different from pev2 or postgres-mcp? pev2 is a visualizer for people. postgres-mcp connects to a live database. slowplan gives an agent ranked findings from plan text, with no database access.

Tested on

PG101, PG102, PG104 to PG112 fired on real plans from a PostgreSQL 17 database with made-up tables, which are in examples/ in both JSON and text. PG103, PG113 and PG114 are only tested on written examples. MCP tool calls were tested through the MCP Inspector. It hasn't been used on a real production query yet.

Contributing

Contributions are welcome, from people and from people working with AI agents. See CONTRIBUTING.md. Good first issues are listed here.

How pull requests work
  1. Open a PR. Fork the repo, work on a branch, and keep it to one change. Write a title that says what changes for users, because it becomes the changelog line: feat: goes under Added and fix: under Fixed.
  2. Automatic check. Code changes need tests, and make test must pass. Changes over 30 lines need a linked open issue (Closes # ), and a PR can have at most 800 changed lines. If something is missing, a comment tells you what to fix.
  3. Review. Claude reviews each PR automatically. Code PRs also get a security review and are tested in a sandbox. The review then merges the PR or asks for changes. PRs that change CI, agent settings, npm or Python dependencies, vendored code or build files can't be merged this way, and a comment says so. The same goes for anything the security review doesn't clear.
  4. Release. A merge that changes what users install becomes a new version within about two hours, with a GitHub Release and, if the project has one, its npm package. Docs and CI changes wait for the next release.

AI disclosure

This project was largely generated with Claude Code and reviewed by its maintainer.

About me

I'm Giulliano Macedo, and I build developer tools at GoTech Solutions. Follow along or get in touch:

If slowplan found your slow query, a star helps others find it.


Built by Giulliano Macedo, GoTech Solutions · LinkedIn · X

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