graphjin vs slayer
Go compiler + runtime exposing databases, warehouses, files and code as one governed GraphQL + MCP graph for agents — catalog-first discovery, allow-lists, built-in agent, standing watches. — versus — Embeddable semantic layer for AI agents: define metrics once, compose them with expressions and time shifts, row-level security and read-only SQL, over MCP, REST, CLI, Python or a Postgres facade.
Both give agents a governed, read-only query surface over databases via MCP and REST with row-level security; Slayer centres on defined metrics, GraphJin compiles GraphQL across raw schemas, files and code.
| graphjin | slayer | |
|---|---|---|
| Stars | 3.2k | 332 |
| Forks | 207 | 45 |
| Language | Go | Python |
| License | Apache-2.0 | MIT |
| Last activity | 5 days ago | yesterday |
| Topics | data | data |
| Curated connections | 4 | 7 |
graphjin — the curator's take
Use it when agents need to query real company data across Postgres/MySQL/Mongo/Snowflake/S3 without raw credentials: discovery-before-action, read-only boundaries, allow-listed queries and audit come built in, and the same binary serves your apps as a GraphQL/REST API. Skip it if you only need one DB behind a single text-to-SQL tool, or want curated metric definitions — a semantic layer fits better; the surface area here is large and opinionated.
slayer — the curator's take
Reach for SLayer when agents keep writing plausible-but-wrong SQL against your warehouse: define columns and metrics once, and agents compose them (ratios, time shifts, alternate aggregations, multi-stage queries) through a search, inspect, query flow instead of free-hand joins, with read-only connections and row-level security handled for them. It imports dbt and Cube definitions, embeds as a Python library, and speaks MCP, REST, Flight SQL and the Postgres wire protocol, so BI tools hit the same definitions. It is the core of Motley's product and still young (a few hundred stars, six contributors). Skip it if you want dashboards out of the box (wrenai) or a layer that builds itself from your existing BI assets (ktx).