The best platform for enterprise MCP connectivity
Run every MCP server, CData-built, custom, and third-party, on one governed platform, with agent tooling, business context, and data handling.
Give every agent and person exactly the tools they need
Run CData-built, custom, and third-party MCP servers in workspaces, and scope each agent’s or person’s tools to their team and use case.
Hundreds of systems, ready to serve.
Ship a Salesforce, SAP, or Snowflake agent today: hundreds of CData-built servers are engineered and maintained for the systems your business runs on, each delivered with curated MCP tools and live read and write, no replication.
Bring any MCP server under governance.
Adopt that GitHub or Datadog MCP server without a separate security review: any HTTPS endpoint speaking MCP registers behind the same governed address and inherits the same identity model, policy, and audit as CData’s own servers.
Compose your own MCP Tool Servers.
Give finance its own server in an afternoon: package a curated set of tools, universal, source, custom, and third-party, into a purpose-built server for one team or one agent, and decide exactly who and what can call each tool. The Agent URL stays stable while admins change what’s behind it, so agents pick up new scope with no redeploy.
Power any use case, from open exploration to precise automation
Let analysts explore freely, run automations that act deterministically, and give every team the same trusted numbers. One tool structure covers the whole spectrum.
Universal tools.
Ask open-ended questions of any source: your agents explore the full data model and find what they need with one tool set that works the same across every system.
Source tools.
Build automations that act: update a ticket, create an invoice, write a record, with deterministic reads and writes for each source, out of the box and governed by the same policies.
Custom tools.
Give every team one trusted number: define a cross-source join or metric once and expose it as a named tool any agent can call. The heavy lifting happens in the data layer, not the prompt.
Trust AI with questions you could only ask your best analyst
Ask “why did EMEA ARR dip last quarter” and get the answer your team would give: every agent works from your definitions, your data model, and your company knowledge, unified into one graph that grounds every tool call.
System context
Every system’s schemas, objects, and relationships, carried by the connectors and known on day one, including the hard ones.
Data model
Curated live datasets, joins, aggregates, and lineage that span sources, modeled once and virtualized over live data rather than replicated.
Semantic definitions
Import existing semantic models or create official metric definitions and business terminology in an AI-guided process.
Company knowledge
Expert judgment and team know-how, imported from documents and captured as people work with agents, approved once into shared context.
Answer questions that used to take a data team a week
Span CRM, ERP, and warehouse in one question, no pipeline, no replication, no waiting: a virtual data layer joins live data across your systems, caches what needs speed, and shapes it into business views AI can trust.
The engine pushes filters, limits, and ~150 functions to the source, so only matching rows travel.
Define logic once and every AI tool queries the same layered views, with lineage back to every source.
Cached parts hit the cache, live parts hit their sources, and the engine joins the results transparently.
The MCP layer decides
Two CData Labs studies, one conclusion: accuracy, safety, and cost are determined by the MCP layer that connects AI to your systems—not by the model.
98.5%
correct through Connect AI
Connect AI answered 98.5% of queries correctly; other MCP providers scored 65–75% on the same set. The difference: Connect AI grounds every request in your schema and business context before it reaches the model. Based on internal testing by CData Software (Q4 2025). No independent third-party verification. Actual accuracy gaps varied among platforms and MCP approaches, testing conducted using sandbox accounts containing known data sets that mirror production account structures. Results may not be representative of performance in live production environments, and results may vary. Organizations should conduct their own independent testing before making purchasing or implementation decisions. 75% range of average accuracy across platforms, results differ by MCP approach.
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178×
cost spread for the same correct answer
Connect AI delivered the same correct answer across models at up to a 178× difference in cost. The difference: Connect AI controls for accuracy and safety, so model choice becomes a cost decision. Based on internal testing by CData Software (Q3 2026). No independent third-party verification. Actual cost gaps varied among models, testing conducted using sandbox accounts containing known data sets that mirror production account structures. Results may not be representative of performance in live production environments, and results may vary. Organizations should conduct their own independent testing before making purchasing or implementation decisions.
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Every system your agents can reach in real-time
Put hundreds of CData connections, plus any third-party MCP server your teams add, all behind the same governed address.
Hundreds of CData-built connectors with live, read and write access
Salesforce
NetSuite
Snowflake
SAP
Jira
Office 365
Workday
HubSpot
PostgreSQLAny HTTPS server speaking MCP, added by your admin, governed like your own.
GitHub
Slack
Stripe
Zendesk
Confluence
Asana
Trello
Monday.com
AirtableFAQ
Questions teams ask
- What makes this the best platform for enterprise MCP connectivity?
- What third-party MCP servers can we add?
- Can an agent reach tools outside its Tool Server?
- Do agents ever see upstream credentials?
- How does the Context Engine change what agents can answer?
- Do cross-system questions require a pipeline or replication?
- Does updating a Tool Server break agent configurations?
- Do we have to migrate our existing MCP setup?
Run your MCP on the best platform for the enterprise
Point your first agent at one governed address and get every MCP server, the right tools, grounded answers, and cross-system queries with governance built in.