Lambë MCP server

Lambë

A query language for structured data that shows you what you're working with.

lam queries JSON, YAML, TOML, HCL, CSV, TSV, and Markdown. Unlike other query tools, it tells you what your query does before you run it — the shape at each pipe stage, which output formats can serialize the result, what would go wrong.

Use it when you don't already know the data: inspecting an unfamiliar API response, auditing a Helm chart, verifying a CI pipeline's assumptions, or asking an AI agent to extract something without guessing at the structure.

$ lam --to toml '.dependencies | keys' pubspec.yaml
Error: TOML output requires a map at the root, got list<string>.
Try appending one of:
  | as(toml)    # Wraps the list under a single-entry map (equivalent to `{items: .}`).

$ lam --to toml '.dependencies | keys | as(toml)' pubspec.yaml
items = ["rumil", "rumil_parsers", "rumil_expressions"]

Queries are bounded and always terminate. No recursion, no lambdas, no def. That's the tradeoff: Lambë doesn't try to be a programming language, so its shape inference, --explain, --schema, and error remediations all work.

Lambë (pronounced "lam-beh") means "language" in Quenya (Tolkien's elvish). The package name is lambe for ASCII compatibility.

Installation

One-line installer (Linux and macOS, no sudo, verifies SHA256 checksums):

curl -fsSL https://raw.githubusercontent.com/hakimjonas/lambe/main/install.sh | sh

This downloads lam and lam-mcp from the latest GitHub release into ~/.local/bin/. Environment variables LAMBEVERSION (pin a version) and LAMBEPREFIX (change install dir) are supported; see the script for details.

Other options:

# From pub.dev (Dart users)
dart pub global activate lambe

# Dart library
dart pub add lambe

# Build from source
git clone https://github.com/hakimjonas/lambe.git && cd lambe
dart compile exe bin/lam.dart -o lam

See Getting started for all installation options.

Shape-aware output

Lambë checks the result of your query against the shape the target format can serialize. When they match, output is produced. When they don't, the error names the required shape and lists query fragments that would bridge it. In an interactive terminal, Lambë offers to apply the chosen fragment and retry in place.

$ lam --to toml '.name' pubspec.yaml
TOML output requires a map at the root, got string.
Try appending one of:
  | as(toml)    # Wraps the scalar under a single-entry map (equivalent to `{value: .}`).

Apply a bridge?
  [1] | as(toml)    # Wraps the scalar under a single-entry map (equivalent to `{value: .}`).
  [q] cancel
> 1
value = "rumil"

The same flow applies to CSV and TSV (which require a list of records at the root) and HCL (which requires a map).

Suggestions surface the intent-level as() form. The explanation names the raw fragment ({value: .}, to_entries, etc.) the bridge composes, so --explain and manual composition stay available to anyone who wants them.

Non-scalar cells in CSV/TSV

By default, nested lists or maps in CSV/TSV cells are rejected — there is no faithful delimited rendering for them. When you need a quick export and lossy is acceptable, pass --flatten-cells json (CLI) or :flatten-cells json (REPL) to encode them as JSON strings inline. Round-tripping the resulting file back into Lambë does not recover the original structure; prefer reshaping the data query-side when fidelity matters.

as(fmt) — bridging in the query language

When the shape of the target format is known up front, as(fmt) performs the bridge inside the query. The combinator is a no-op when the input already satisfies the target, applies a single curated bridge when one exists, and lists the candidates when more than one could apply.

$ lam --to toml '.dependencies | as(toml)' pubspec.yaml
rumil = "^0.6.0"
rumil_parsers = "^0.6.0"
rumil_expressions = "^0.6.0"

Shortened. The full README is on GitHub.