MCP server: One MCP server.

Lagaam

@lagaam-aiMCP server · External

Stops an agent's Trino or Pinot query before it runs if it costs too much or reads outside its grant

Databasesv0.2.5Apache-2.0Python
Freeno charge per call

Runs on your machine from its package; the steps are below.

Lagaam — every query priced before it runs
From the README · 1 of 3

What it does

  1. Reads
  2. Writes
  3. High impact

Not assessed yet.

What it costs

Free

Odel charges nothing per call. The publisher may charge for its own service.

Runs locally over stdio

This server isn't hosted — your MCP client launches it from a package registry. Use one of the commands below, or drop the config into your client (e.g. Claude Desktop).

PyPIlagaamv0.2.5

Run

uvx lagaam

MCP client config

{
  "mcpServers": {
    "lagaam": {
      "command": "uvx",
      "args": [
        "lagaam"
      ]
    }
  }
}
README10 min read

Lagaam — every query priced before it runs

One agent query shouldn't stall everyone's Trino. On a shared cluster, a missing partition filter or an accidental cross join doesn't cost you a bill — it costs everyone else their queries. Lagaam is an MCP server that sits between your AI agents and your lakehouse (Trino and Apache Pinot): every query is schema-grounded, priced from the engine's own plan before it runs, checked against a budget, and audited — and the bad one is refused before it runs, with a fix the agent can act on.

Lagaam demo: SELECT * rejected, an oversized join blocked pre-execution, a scoped query running

Real session, real Trino, nothing mocked — reproduce it with uv run --project server python examples/demo.py.

Lagaam demo: a consuming Pinot segment priced at its flush threshold, a keyless join blocked, the same join admitted on a proven upsert key

Real session, real Pinot 1.5.1 realtime table, nothing mocked — reproduce it with uv run --project server python examples/demo_pinot.py.

The problem

Agents write syntactically-valid, catastrophic SQL, and on a shared cluster the damage isn't theirs alone. A missing partition filter turns into a full scan that ties up every worker; an accidental cross join fills worker memory while everyone else's queries wait behind it; a retry loop runs it again. A SELECT * drags 40 columns into a context window that needed 2. The usual fix is to not give agents database access at all.

Lagaam gives them access with reins on:

  • Cost is a quotation, not a bill. Every query is priced from the engine's own plan before execution — EXPLAIN (TYPE IO) for the bytes it would scan, EXPLAIN (TYPE LOGICAL) for the widest row count any operator would build (the number a cross join blows and a LIMIT cannot hide). Over budget → blocked, with the number and the fix.
  • Un-estimable means no. No table statistics, a self-join that breaks the estimate, a passthrough the planner can't see — the gate fails safe instead of hoping.
  • Read-only, enforced in the AST. Single SELECT only. No DDL/DML, no multi-statement injection, no SELECT *, no table-function passthrough, and a LIMIT is injected when missing. Validated SQL is re-rendered, so what runs is exactly what was checked.
  • Agents ground themselves. list_catalogs and describe_table return exact names, types, and row estimates — scoped to the agent's table grant, so the agent never learns names it isn't allowed to touch.
  • Results are verified before they're trusted. Zero rows, truncated pages, all-NULL columns — the agent gets a warning with a next action, not a silently misleading answer.
  • Every call is audited. One JSONL line per tool call: who, what, allowed or denied, and why.

Doesn't Trino already limit this?

It limits a query once it is running. Lagaam refuses it before it starts. Keep both.

ActsWhat the agent seesCatches a cross join that reads little
query.max-scan-physical-bytesduring execution: terminated once the bytes are scanneda query failureno — it counts bytes read, not rows built
query.max-execution-timeduring execution: terminated after the time is spenta query failureonly after it has held the cluster that long
Resource groups (hardPhysicalDataScanLimit, softMemoryLimit, …)on the next query: new queries queue once the group is over its shareits later queries waitno — the running query continues
Lagaambefore execution, from EXPLAINa refusal with the number and the fixyes — it prices the rows the widest step would build

Measured on Trino 476: SELECT o.orderkey, l.partkey FROM tpch.tiny.orders o CROSS JOIN tpch.tiny.lineitem l LIMIT 10 reads 676,575 bytes by Trino's own plan — any scan cap above 0.7 MB lets it run — and would build 902,625,000 rows. Lagaam refuses it before it runs: "This query would build 902,625,000 rows at its widest step, over your budget of 50,000,000 … a LIMIT will not help — join on a column with more distinct values, or filter each side before the join."

Resource groups stay your backstop for everything that does reach the cluster; Lagaam is the gate in front of it for agent traffic.

What about other database MCP servers?

They're good servers that do a different job: keep the agent read-only and bound what comes back. Lagaam does that too, and also prices the query first.

Read-onlyRow capTimeoutChecks the plan before running
tuannvm/mcp-trinoon by defaultresults truncated while fetching (TRINO_MAX_ROWS)during execution (TRINO_QUERY_TIMEOUT)no — explain_query shows the agent a plan; it doesn't gate execute_query
startreedata/mcp-pinotalways on, parsed before executionLIMIT rewritten before execution, paged resultsduring execution (PINOT_QUERY_TIMEOUT, 60 s)no
bytebase/dbhubopt-in (readonly): keyword check plus the database's own read-only transactionopt-in (max_rows), injected as LIMIT/TOPopt-in (query_timeout), during executionno — opt-in explain_sql shows a plan; it doesn't gate execute_sql
Lagaamalways on, parsed before execution1,000 by default; a bigger LIMIT is lowered before it runsduring execution (LAGAAM_QUERY_TIMEOUT, 300 s)yes — scan bytes and widest-step rows from EXPLAIN; over budget is refused

Catch rate

11 queries an LLM agent plausibly writes — full scans, SELECT *, DDL, injection attempts, oversized joins, out-of-grant reads. A raw MCP wrapper submits all of them to the engine. Lagaam stops 11/11 before execution while the well-scoped control query runs untouched. Reproduce: benchmarks/catch_rate.py → results.

Quickstart

Against the Trino you already have (TRINO_PORT / TRINO_USER if yours aren't 8080 / lagaam):

bash
TRINO_HOST=trino.internal LAGAAM_ALLOWED_TABLES=hive.sales.orders uvx lagaam   # MCP server on stdio

Or try it on a demo warehouse:

bash
git clone https://github.com/lagaam-ai/lagaam && cd lagaam
docker compose -f examples/docker-compose.yml --profile trino up -d   # demo warehouse
cd server && uv sync
LAGAAM_ALLOWED_TABLES=tpch.tiny.orders,tpch.tiny.lineitem \
  uv run python -m lagaam                                             # MCP server on stdio

For Pinot, --profile pinot brings up the batch quickstart and --profile pinot-realtime up -d brings up a Kafka-fed streaming one — run examples/pinot-realtime/bootstrap.sh after it to create the topics, tables and feed. Then start the server with LAGAAM_ENGINE=pinot.

Wire it into any MCP client (Claude Code, Claude Desktop, or your own agent):

json
{
  "mcpServers": {
    "lagaam": {
      "command": "uvx",
      "args": ["lagaam"],
      "env": {
        "TRINO_HOST": "localhost",
        "LAGAAM_MAX_SCAN_BYTES": "5368709120",
        "LAGAAM_ALLOWED_TABLES": "hive.sales.orders,hive.sales.customers"
      }
    }
  }
}

In Claude Code, install it as a plugin instead:

/plugin marketplace add lagaam-ai/lagaam
/plugin install lagaam@lagaam

It asks for the tables to allow (LAGAAM_ALLOWED_TABLES) and your Trino host, port and user (localhost / 8080 / lagaam if you leave them). From a shell, pass them as flags:

bash
claude plugin marketplace add lagaam-ai/lagaam
claude plugin install lagaam@lagaam \
  --config allowed_tables=hive.sales.orders --config trino_host=trino.internal

On Pinot, pick engine=pinot and set the controller and broker URLs (http://localhost:9000 / http://localhost:8000 if you leave them):

bash
claude plugin install lagaam@lagaam --config engine=pinot \
  --config allowed_tables=pinot.default.baseballStats \
  --config pinot_controller_url=http://pinot.internal:9000 \
  --config pinot_broker_url=http://pinot.internal:8099

Other LAGAAM_* settings, and PINOT_USER / PINOT_PASSWORD for a Pinot with auth, are read from the environment you start claude in.

The agent gets three tools — list_catalogs, describe_table, query_data — and cannot reach the engine any other way.

Configuration

Env varMeaningDefault
LAGAAM_ALLOWED_TABLESComma list of catalog.schema.table grantsrequired
LAGAAM_ALLOW_ALL_TABLEStrue to run with no grant at alloff
LAGAAM_AGENT_NAMEIdentity stamped on the audit trailanonymous
LAGAAM_MAX_SCAN_BYTESScan-bytes budget per query, pre-execution50 GiB
LAGAAM_MAX_ROWSScanned-row estimate budget per queryungated
LAGAAM_MAX_INTERMEDIATE_ROWSRows the engine would build at its widest step — not rows returned, so a LIMIT doesn't lower it50,000,000
LAGAAM_MAX_RETURNED_ROWSRows returned to the agent per query — unset, the server applies its own 1000-row cap, and a bigger LIMIT in the query is lowered to it before it runs1000 (max 100000)
LAGAAM_QUERY_TIMEOUTWall-clock seconds per query300
LAGAAM_METADATA_TTLMetadata cache TTL, seconds300
LAGAAM_AUDIT_LOGAudit JSONL file pathstderr
TRINO_HOST / TRINO_PORT / TRINO_USERTrino coordinatorlocalhost / 8080 / lagaam

The server will not start without LAGAAM_ALLOWED_TABLES. An agent that can reach every table in every catalog is the thing this exists to prevent, so that has to be asked for — set LAGAAM_ALLOW_ALL_TABLES=true if you mean it.

The budget dimensions above apply whether or not you set them. Leaving LAGAAM_MAX_SCAN_BYTES and LAGAAM_MAX_INTERMEDIATE_ROWS unset gives you their defaults, not an open gate — an unconfigured server refuses what it cannot afford rather than waving it through. If queries are being denied and you expected no limits, that is why; raise the dimension you mean to raise.

Cost quotes come from the engine's own plan estimates, and those need table statistics: a table without stats cannot be priced, so its queries are refused rather than guessed at. Run ANALYZE on your tables before pointing an agent at them — a connector that has no statistics at all is effectively unusable through the gate. That is deliberate: a query nobody can size is exactly the kind that stalls a shared cluster.

How it works

A QueryEngine port with a Trino adapter and a native Pinot adapter — grounding, execution, and a synthesised cost quotation for both OFFLINE and REALTIME tables. Every query_data call walks one pipeline: validate (sqlglot AST) → table allowlist → cost quotation → budget gate → execute (row cap + timeout) → verify → audit.

On Trino, the quote is the engine's own plan, not a guess from the SQL text: EXPLAIN (TYPE IO) prices the bytes a query would scan, and EXPLAIN (TYPE LOGICAL) prices the widest row count any operator would build — the number a cross join blows and a LIMIT cannot hide.

Pinot gives no such plan — every table scan reports the same placeholder row count whatever the table holds, and no endpoint reports bytes at all — so its quote is synthesised instead: from static segment metadata, the broker's own pruning oracle (how many segments survive the predicate), and the plan's join/union shape. A consuming (REALTIME) segment, which the controller reports as empty mid-flight, is priced at the stream's own flush threshold instead of zero. A join is charged its bound rather than the product wherever the catalog can prove the join key. See ADR 0008 and ADR 0009.

Details in docs/architecture.md; the longer story in docs/vision.md.

Status

v0.2.5 — on PyPI as lagaam, listed in the MCP Registry as io.github.lagaam-ai/lagaam, installable as a Claude Code plugin (lagaam@lagaam). Trino adapter, schema tools, plan-based cost guard, query budgets, read-only enforcement, per-agent allowlists, result verification, audit log. 1,189 unit + 212 integration tests (live Trino 476 and Pinot 1.5.1, batch and realtime), mypy strict. LAGAAM_ENGINE=pinot starts the native Pinot adapter: grounding, execution and a quotation synthesised from segment metadata and the broker's own pruning oracle, for OFFLINE and REALTIME tables alike — a consuming segment is charged at the stream's flush threshold, and a join is charged its bound rather than the product wherever the catalog proves the key. On deck (roadmap): post-execution actuals on the audit line, then a Kubernetes control plane — agents as CRDs with token/dollar budgets and kill switches.

Apache 2.0.

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