Solution · AI data supply

Give AI systems current enterprise data

Keep the stores behind retrieval and agent workflows synchronized with operational systems, and expose Core Hub pipelines and SQL to MCP clients under the caller's own permissions.

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OPERATIONAL SOURCES CAPTURED CONTINUOUSLY PostgreSQL · orders MongoDB · catalog Db2 for i · ledger log, journal, and change-stream capture continuous CDC Gluesync Core Hub one control plane row filters field functions defined functions only the rows and fields you allow leave the source RETRIEVAL STORES MongoDB · Couchbase Parquet in object storage kept current by CDC MCP CLIENT RBAC /mcp · /mcp/http pipelines · SQL tools caller's own role
  1. 01 Synchronize the retrieval store
  2. 02 Send only what belongs
  3. 03 Connect agents through MCP

The challenge

Models answer from whatever you last exported

Retrieval quality depends on how recent the underlying store is, and most AI data supply is still a scheduled dump out of the systems that hold the record.

01 / Staleness

Exports date immediately

A nightly extract into a retrieval store means answers reflect yesterday's inventory, pricing, or case status.

02 / Fragmentation

Context lives in several engines

The records a model needs are spread across relational, NoSQL, and file-based systems with different access paths.

03 / Governance

Agent access outruns permissions

Wiring an assistant straight into production databases spreads credentials and sidesteps the roles already defined.

How it works

Synchronize the stores, then expose them safely

Gluesync keeps AI-facing stores current with change data capture, shapes records on the way through, and lets MCP clients reach Core Hub without new privileges.

  1. 01

    Feed

    Synchronize the retrieval store

    Continuous CDC keeps document databases, object storage, and analytical targets aligned with the operational source.

  2. 02

    Shape

    Send only what belongs

    Row filters, field functions, and user-defined functions decide which records and fields ever leave the source.

  3. 03

    Expose

    Connect agents through MCP

    The embedded Core Hub MCP server presents pipeline, monitoring, and SQL tools to MCP clients over standard transports.

Gluesync capabilities

A supply line for retrieval and agent workflows

Gluesync keeps the data current and queryable for the layer that builds your embeddings and prompts, rather than generating them itself.

01

Core Hub MCP server

An embedded Model Context Protocol server runs inside Core Hub and exposes pipeline, observability, and SQL tools to MCP clients.

  • SSE and streamable HTTP transports
  • Caller's bearer token and RBAC enforced
  • Read-only and allow-list modes

Core Hub MCP server

02

Continuously synchronized stores

Land current records where your retrieval layer already reads them, from document databases to object storage.

  • MongoDB and Couchbase targets
  • Parquet in S3, ADLS Gen2, and Cloud Storage
  • Composed document keys

MongoDB agent Custom document keys

03

Payload shaping and filtering

Decide at the pipeline level which rows and fields reach an AI-facing store, at both snapshot and CDC time.

  • Inclusive row-level filters
  • Field functions on values
  • User-defined functions

Data filtering User-defined functions

Point your models at data that keeps moving

Start a trial or talk with MOLO17 about the stores, filters, and access model behind your AI workloads.

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