CONTEXT STORE

One context layer for every agent, across every business system

Semantic search across your entire business. The Context Store replicates, unifies, and optimizes data for agentic discovery. Available today for Snowflake and BigQuery users.

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~/AIRBYTE-AGENT — TERMINAL

WHY AGENTS STRUGGLE IN PRODUCTION

MCPs give agents access.
They do not give agents a map.

Every answer becomes a live crawl across Salesforce, Zendesk, Stripe, and the rest. The agent burns tokens, hits rate limits, and can only find what it already knows to ask for.

Token waste

Raw API responses pile up in the context window before the agent starts reasoning. It spends tokens cleaning data instead of answering.

Latency stacking

Every source is another round trip. Five systems means five sequential API calls, each with its own rate limits, before the agent can begin.

No map

APIs only answer questions you already know how to ask. The agent can't see what data exists or how it connects, so it never asks for what it doesn't know is there.

WHAT A QUERY COSTS

Your agent receives a query about Flowtech.
Here's what happens.

Without Airbyte5 systems = 5 live calls

Round trip. Renewal date buried in dozens of fields.

Salesforce API

Round trip. Rate-limited. Retry.

Zendesk MCP

Round trip. Completely different schema to parse.

Stripe API

Three raw payloads dumped in. Tokens burned before reasoning starts.

Gong MCP

Three different "Flowtech" records reconciled on the fly.

Linear MCP

Five round trips before the agent can begin to reason. Slow, expensive, and brittle the moment an API rate-limits or returns partial data.

With Airbyte1 search, pre-linked

context store

One query returns the unified Flowtech record, renewal, support, payments, already connected.

reason

The agent reasons immediately and answers.

One round trip. Fast, cheap, reliable.

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How it works

The Context Store owns the knowing.
Connectors own the doing.

READ & SEARCH

Context Store

Business entities replicated into a searchable index on your warehouse. Agents run semantic search across unified context in a single call. No live crawl, no stitching.

WRITE & ACT

Real-time Connectors

When an agent needs to act, Airbyte connectors handle real-time reads and writes back to the source systems.

How they work together

Your agent discovers what it needs through the Context Store, then acts on it through connectors. It always knows where to look and always has a direct path to act.

73%
fewer tokens on a single query
33%
fewer tool calls vs. native vendor MCPs
83%
cost savings on multi-source queries

run the benchmark yourself Talk to Us

USE CASES

What agents can do with the Context Store

Cross-system questions your team already asks, answered by agents against indexed context, with live actions when needed.

CROSS_SYSTEM_QUERY.PY

tickets = await zendesk.execute("tickets", "context_store_search",
    params={"query": {"filter": {"eq": {"status": "open"}}}})

invoices = await stripe.execute("invoices", "context_store_search",
    params={"query": {"filter": {"eq": {"status": "past_due"}}}})

RESPONSE.JSON

# tickets  (zendesk)
[
  { "id": 4892, "subject": "Checkout API failing",   "status": "open" },
  { "id": 4891, "subject": "Dashboard export empty", "status": "open" }
]

# invoices  (stripe)
[
  { "id": "in_1P8x", "customer": "Flowtech",  "amount_due": 12480, "status": "past_due" },
  { "id": "in_1P8y", "customer": "NorthPeak", "amount_due":  4200, "status": "past_due" }
]
// ─── truncated ─────────────────────────────────────

CONTEXTUAL_ACTION.PY

issue = await linear.execute("issues", "create",
    params={"team_id": "<team_id>", "title": "Onboard Acme Corp"})

await slack.execute("messages", "create",
    params={"channel": "#customer-success", "text": "Acme closed. Onboarding started."})

RESPONSE.JSON

# linear.issues.create  (linear)
{
  "id": "LIN-4821",
  "title": "Onboard Acme Corp",
  "status": "created"
}

# slack.messages.create  (slack)
{
  "channel": "#customer-success",
  "ts": "1737292811.0042",
  "status": "posted"
}
// ─── truncated ─────────────────────────────────────

ACCOUNT_LOOKUP.PY

deal = await salesforce.execute("opportunities", "context_store_search",
    params={"limit": 1, "query": {"filter": {"eq": {"account_name": "Acme Corp"}}}})

tickets = await zendesk.execute("tickets", "context_store_search",
    params={"query": {"filter": {"eq": {"organization": "Acme Corp"}}}})

RESPONSE.JSON

# deal  (salesforce)
{
  "id": "0065f00000ABcDe",
  "account_name": "Acme Corp",
  "stage": "Negotiation",
  "amount": 148000,
  "close_date": "2026-08-30"
}

# tickets  (zendesk)
[
  { "id": 4892, "subject": "Checkout API failing",   "priority": "urgent" },
  { "id": 4877, "subject": "SSO login loop",         "priority": "high" },
  { "id": 4861, "subject": "Webhook retries missing", "priority": "normal" }
]
// ─── truncated ─────────────────────────────────────

FILTERED_RETRIEVAL.PY

urgent = await zendesk.execute("tickets", "context_store_search",
    params={"limit": 20, "query": {"filter": {"eq": {"priority": "urgent"}}}})

RESPONSE.JSON

# urgent  (zendesk)
[
  { "id": 4892, "subject": "Checkout API failing",      "priority": "urgent", "organization": "Acme Corp" },
  { "id": 4885, "subject": "Data pipeline stalled",     "priority": "urgent", "organization": "Kestrel Co" },
  { "id": 4879, "subject": "Billing portal 500 errors", "priority": "urgent", "organization": "Meridian" },
  { "id": 4870, "subject": "OAuth callback timing out", "priority": "urgent", "organization": "Flowtech" }
]
// ─── truncated ─────────────────────────────────────

ENTITY RESOLUTION

Sarah Chen in Salesforce is sarah@flowtech.com in Stripe is Ticket #4892 in Zendesk.

The Context Store features entity resolution. Records are matched and merged across systems at the data layer.

Your agent queries one entity, not three fragments.

How is the Context Store different from connecting vendor MCP servers?

Vendor MCP servers expose one system at a time. Each call returns raw API payloads your agent must page through, rate-limit, and stitch together. The Context Store replicates a curated subset of entities from every connected source into one searchable layer, so agents query unified business context in a single call—with indexed search, cross-source queries, and automatic refresh.

Isn't this just a warehouse?

Warehouses centralize data for analysis. They aren't built for the millisecond, single-query retrieval agents need to reason in real time. The Context Store sits on top of your warehouse to provide high speed, accurate semantic search and entity resolution across all of your systems.

Isn't this just RAG?

RAG chunks documents and retrieves passages. The Context Store indexes structured business entities and their relationships, so an agent can ask about an account and get its deal, tickets, and payment state as one object.

Is the Context Store a vector database?

No. It's a searchable replica of structured business entities on your warehouse, not an embedding store. Agents run semantic search across entities and relationships Airbyte replicates from your connected sources.

How much does the Context Store reduce token usage?

Measured across Gong, Linear, Salesforce, Slack, and Zendesk connectors, the Context Store reduces token usage by up to 80% compared to direct API calls (up to 90% for Zendesk) and cuts tool calls by up to 40%, because agents query pre-indexed context instead of paging live APIs into the LLM context window.

Can't we build this in-house?

You can stitch connectors, sync jobs, entity resolution, and search yourself, but that stack is the product. The Context Store ships curated replication, continuous refresh, and semantic search on your warehouse, accessible via MCP or the Airbyte UI. Spend time on agent behavior, not plumbing.

What happens when pre-materialized data is stale?

The Context Store refreshes on a recurring schedule from your connected sources. For reads that must be fresher than the last sync, agents can still call through connectors to the live system while keeping indexed context as the default path for search and multi-source questions.

Your agents don't need more tools. They need context.

Semantic search across your entire business. Set up once, query from any agent.

Talk to Us Read the Docs

One context layer for every agent, across every business system

MCPs give agents access.
They do not give agents a map.

Token waste

Latency stacking

No map

Your agent receives a query about Flowtech.
Here's what happens.

The Context Store owns the knowing.
Connectors own the doing.

Context Store

Real-time Connectors

Better context. Faster agents.

What agents can do with the Context Store

Cross-system queries

Contextual actions

Account lookup

Filtered retrieval

Sarah Chen in Salesforce is sarah@flowtech.com in Stripe is Ticket #4892 in Zendesk.

FAQ

Your agents don't need more tools. They need context.

Build with Airbyte

One context layer for every agent, across every business system

MCPs give agents access.They do not give agents a map.

Token waste

Latency stacking

No map

Your agent receives a query about Flowtech.Here's what happens.

The Context Store owns the knowing.Connectors own the doing.

Context Store

Real-time Connectors

Better context. Faster agents.

What agents can do with the Context Store

Cross-system queries

Contextual actions

Account lookup

Filtered retrieval

Sarah Chen in Salesforce is sarah@flowtech.com in Stripe is Ticket #4892 in Zendesk.

FAQ

Your agents don't need more tools. They need context.

MCPs give agents access.
They do not give agents a map.

Your agent receives a query about Flowtech.
Here's what happens.

The Context Store owns the knowing.
Connectors own the doing.