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Lagaam

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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. A query's line puts the quote next to what the engine says it actually read, so you can see how far off the estimate was before you loosen or tighten a budget.

Related MCP server: dst

Doesn't Trino already limit this?

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

Acts

What the agent sees

Catches a cross join that reads little

query.max-scan-physical-bytes

during execution: terminated once the bytes are scanned

a query failure

no — it counts bytes read, not rows built

query.max-execution-time

during execution: terminated after the time is spent

a query failure

only 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 share

its later queries wait

no — the running query continues

Lagaam

before execution, from EXPLAIN

a refusal with the number and the fix

yes — 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-only

Row cap

Timeout

Checks the plan before running

tuannvm/mcp-trino

on by default

results 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-pinot

always on, parsed before execution

LIMIT rewritten before execution, paged results

during execution (PINOT_QUERY_TIMEOUT, 60 s)

no

bytebase/dbhub

opt-in (readonly): keyword check plus the database's own read-only transaction

opt-in (max_rows), injected as LIMIT/TOP

opt-in (query_timeout), during execution

no — opt-in explain_sql shows a plan; it doesn't gate execute_sql

Lagaam

always on, parsed before execution

1,000 by default; a bigger LIMIT is lowered before it runs

during 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):

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

Or try it on a demo warehouse:

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):

{
  "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:

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):

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, the Trino login (TRINO_PASSWORD or TRINO_JWT, plus TRINO_VERIFY for a private CA), and PINOT_USER / PINOT_PASSWORD for a Pinot with auth, are read from the environment you start claude in, so a password never sits in the plugin's config.

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

Configuration

Env var

Meaning

Default

LAGAAM_ALLOWED_TABLES

Comma list of catalog.schema.table grants

required

LAGAAM_ALLOW_ALL_TABLES

true to run with no grant at all

off

LAGAAM_AGENT_NAME

Identity stamped on the audit trail

anonymous

LAGAAM_MAX_SCAN_BYTES

Scan-bytes budget per query, pre-execution

50 GiB

LAGAAM_MAX_ROWS

Scanned-row estimate budget per query

ungated

LAGAAM_MAX_INTERMEDIATE_ROWS

Rows the engine would build at its widest step — not rows returned, so a LIMIT doesn't lower it

50,000,000

LAGAAM_MAX_RETURNED_ROWS

Rows 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 runs

1000 (max 100000)

LAGAAM_QUERY_TIMEOUT

Wall-clock seconds per query

300

LAGAAM_METADATA_TTL

Metadata cache TTL, seconds

300

LAGAAM_AUDIT_LOG

Audit JSONL file path

stderr

LAGAAM_ENGINE

pinot to run the native Pinot adapter

trino

PINOT_CONTROLLER_URL / PINOT_BROKER_URL

Pinot controller and broker

http://localhost:9000 / http://localhost:8000

PINOT_USER / PINOT_PASSWORD

Basic-auth login for Pinot

unset (no login)

TRINO_HOST / TRINO_PORT / TRINO_USER

Trino coordinator

localhost / 8080 / lagaam

TRINO_PASSWORD

Password for TRINO_USER, for a cluster that wants a login

unset (no login)

TRINO_JWT

JWT to log in with instead of a password — set one or the other, not both

unset

TRINO_HTTP_SCHEME

http or https

https once a password or JWT is set, else http

TRINO_VERIFY

Check the cluster's TLS cert: true, false, or the path of your CA bundle (PEM) for a private CA

true

A shared Trino with a login works the same way. Set TRINO_PASSWORD (or TRINO_JWT) and lagaam talks https, since Trino won't take a password over plain http; set TRINO_PORT to the cluster's https port too (often 443 or 8443). A login the cluster refuses tells the agent so, without the password, and a password and a JWT both set stop the server at startup rather than guessing which one you meant. Try it locally against a Trino that wants both: examples/trino-auth/setup.sh, then docker compose -f examples/docker-compose.yml --profile trino-auth up -d.

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.

What it doesn't do

  • One agent per server process, over stdio. Identity and grant come from the environment at startup; there is no HTTP transport or per-request token. Run one lagaam per agent.

  • No stats, no answer. A table without statistics can't be priced, so its queries are refused (see above).

  • Per query, not per day. Budgets bound each query; there is no running total across an agent's session.

  • Trino and Pinot only. Other engines would need their own adapter behind the same QueryEngine port.

  • Actuals are recorded, never enforced. The audit line shows what a query really read next to its quote; nothing is cut off mid-run on those numbers — that is what LAGAAM_QUERY_TIMEOUT and your engine's own limits are for.

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

v1.0.0 — 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 with post-execution actuals, https + password/JWT login for a shared Trino. 1,243 unit + 219 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.

The MCP server is feature-complete: what's here is what v1 is, and new work is bug fixes and engine compatibility. The Kubernetes control plane in the roadmap is not scheduled.

Apache 2.0.

Available Tools

3 tools
describe_tableDescribe tableA
Read-only

Get the exact columns and types of one table. Read-only.

    Always describe a table before querying it; column names you have
    not seen here are guesses. It reads the engine's metadata and
    statistics, never the table's rows. A table outside your grant is
    refused before the engine is asked; a missing one errors with a
    pointer to list_catalogs. Answers are cached, 5 minutes by default,
    so a new column can lag. row_estimate is the engine's row-count
    statistic, null when it has none or can't be trusted (views, tables
    without stats, Pinot tables with a realtime part). Column comments
    are null when unset, and always on Pinot.
    

Inputs: table (required), schema (required), catalog (required). Returns: Grounding card for one table: identity + columns.

list_catalogsList catalogsA
Read-only

List every catalog, schema, and table you are allowed to query.

Call this first to ground yourself before describing tables or writing SQL — table names you have not seen here are guesses.

Inputs: no named parameters. Returns: catalogs

query_dataQuery dataA
Read-only

Run a read-only SELECT and get the rows back.

    Write a single SELECT in the engine's dialect. The query is checked
    for safety, priced against your budget, and executed with a row cap —
    so name the columns you need (no SELECT *), and add WHERE filters to
    keep the scan small. At most 1,000 rows come back by default (a
    larger LIMIT is lowered to the cap), and `truncated` marks a result
    the cap cut off. A query that touches any table outside your grant
    is refused before it runs. If it is rejected, the message says what
    to fix. Describe the tables first so column and table names are exact.
    

Inputs: sql (required). Returns: Rows returned to the agent, capped to a row budget. ``truncated`` says the cap…

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A4.4/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool targets a distinct step in the metadata-to-query workflow: catalog discovery, table introspection, and query execution. The descriptions explicitly state the intended ordering and cross-reference each other, leaving no realistic chance of misselection.

    Naming Consistency5/5

    All three names follow a uniform snake_case verb_noun pattern (list_catalogs, describe_table, query_data). The verbs are accurate and non-overlapping.

    Tool Count4/5

    Three tools is lean but each is essential to the read-only query lifecycle, so nothing is redundant. It sits at the low end of the comfortable range, with no room for auxiliary operations like budget or explain previews.

    Completeness4/5

    Discover-schema, describe-table, and run-SELECT cover the core read-only workflow end to end, including safety refusals and row caps. Minor gaps exist — no way to preview query cost/budget or search schema objects by name — but agents can work around them.

    Maintenance

    ActivityActive
    ResponsivenessLimited data

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