Your agent needs a way to finish the job across your systems.
An AI agent integration platform supplies the connections and executable actions that let an agent read records, make changes, and move work between applications. Start your evaluation with Workato, Monarch, Composio, and Merge Agent Handler. Each addresses that integration problem through a different approach, explained below.
Keep a separate decision for where you build and run the agent. Microsoft and Google offer broader suites. Building directly with OpenAI or Claude is another real option. Those choices can sit alongside a dedicated integration layer when the required tool interfaces and authorization work together.
The useful comparison is the work each option can complete in your environment, the controls around it, and the implementation your team still owns.
Start with the operations your workflow needs
A pre-built connector handles a connection and exposes a defined set of operations. An application name in a catalogue is a starting point. You still need the right actions, fields, and permissions.
Consider a support escalation. The agent finds the customer in a CRM, reads an order, checks an entitlement, and creates an approved service request in an internal system. Finding the customer is one part of that job.
Walk through the process with the person who does it today. Include the spreadsheet they use to reconcile records and the custom field they check before making a change. Those details belong in your evaluation.
Breadth describes how many systems a platform connects. Depth describes what it can do inside each one with the access your company will grant.
Compare the integration platforms first
These four belong on an agent integration shortlist. Their fit depends on what you already have and where the missing work sits.
| Platform | How it supplies agent actions | What to test on your workflow |
|---|---|---|
| Workato | Integration infrastructure with tools exposed through Enterprise MCP | Reuse of existing integrations; exact operations and fields; required extensions |
| Composio | Application tools with managed authentication and user-scoped connections | Required toolkit actions; account identity; the workflow logic around tool calls |
| Merge Agent Handler | Curated Tool Packs, user credentials, and an MCP endpoint | Tools included in each pack; per-user access; orchestration in your application |
| Monarch | Application discovery, a Product Graph of executable operations, and cross-system orchestration | What discovery captures and verifies in your account, including less-documented application behaviour |
Workato: reuse integration work you already trust
Workato Enterprise MCP exposes business tools to compatible agents and provides authentication, configurable rate limits, and activity logs. Its documentation also describes end-user credentials for external calls. Check the configured identity path when evaluating permissions.
Workato also builds genies that orchestrate workflows dynamically, so its platform spans agent building and integration. If your team already operates the required integrations, extending that investment deserves a serious look. Workato also supports custom HTTP requests through its connector SDK, so a missing pre-built action can have a practical extension route.
Price the work to identify, implement, and maintain that extension. Our Monarch and Workato comparison examines where reusing integration infrastructure and discovering application behaviour lead to different choices.
Composio: connect your agent to application tools
Composio's authentication documentation describes reusable authentication configurations, scopes, and connected accounts associated with a user ID. Its agent sessions handle authentication, while toolkits supply application-specific tools.
Include it when your team is building an agent and needs application access without implementing every authentication flow itself. Run the required actions against your actual fields and account configuration. Our Monarch and Composio comparison goes deeper into that evaluation.
Merge Agent Handler: curate the tools an agent can call
Merge Agent Handler stores credentials per registered user and exposes selected tools through Tool Packs and MCP. Its implementation guide assigns orchestration to your backend.
Evaluate this product directly. Merge's Unified API is a separate offering, and a comparison based only on a common data schema misses what Agent Handler supplies. It merits a place when you want to control the tools available to an agent while retaining your own application logic.
Monarch: discover the application behaviour the job depends on
Monarch's Product Graph maps application operations, schemas, prerequisites, and permissions through authenticated access. It includes public APIs, private web endpoints, and UI paths. Monarch then orchestrates agentic workflows across those captured and verified operations, maintaining the application knowledge they depend on.
That approach is worth testing when a workflow depends on a custom installation, poorly documented behaviour, or several systems whose dependencies take time to understand. Coverage follows the connected account's permissions and what discovery captures and verifies.
Bring the difficult operation into the pilot. Your team still defines the business rules, authoritative records, and approval requirements.
Look beyond the first connected process
An enterprise can have many software licences and still give its agents access to only a small part of the work. Evaluate how the platform expands that usable coverage, and what it lets you build once the operations are available.
Monarch discovers the connected applications, maintains their verified paths, and orchestrates agentic workflows across them. The purpose of the map is to let agents carry out complex work that previously required someone to understand and operate several products manually.
| Expansion step | What to establish in a Monarch evaluation |
|---|---|
| Add a product | Mapping typically takes hours once suitable access is available; test the required depth and complexity |
| Add a workflow | Inference over mapped operations can build a new workflow in minutes; define its rules and verify the completed result |
| Reuse a process pattern | Adapt established practices to your records, policies, and approvals |
| Keep operating through change | Test maintenance of shared application paths and the workflows that depend on them |
Mapping and workflow creation are parts of implementation. Security review, access preparation, and production testing need their own plan. Retain your chosen model and cloud services where they fit, and decide which platform owns each workflow's execution and recovery.
Treat Microsoft and Google as broader build choices
Microsoft's products have different jobs. Copilot Studio provides a low-code agent builder. Foundry Agent Service supports managed agent deployment and tools. Fabric data agents supply access to organizational data; their Copilot Studio connection is documented as preview.
Those capabilities can make a Microsoft-centred implementation sensible. Define which product owns the agent, which supplies data, and which executes each application change. The Microsoft Copilot Studio, Foundry, and Fabric comparison works through that separation.
Google's Gemini Enterprise Agent Platform, an evolution of Vertex AI, spans agent building, deployment, and governance. Evaluate that suite alongside your existing Google investment, then verify the integration routes needed for each operation. Our Google Gemini comparison covers the build decision in more detail.
Building directly with OpenAI or Claude is a real alternative
OpenAI supports connectors and remote MCP servers. Claude supports tool use, including functions whose execution your application handles.
For a narrow workflow with understood APIs and a team that can own the code, direct implementation may be the right choice. Compare the complete cost: authentication, validation, approvals, retries, logging, and maintenance, alongside model usage.
Our guide to enterprise actions with Claude and OpenAI explains those responsibilities. If the usable operation sits in the interface, include browser access in the design and test computer-use completion and recovery.
n8n's AI Agent node and Relevance AI's agent and tool builders are adjacent choices for assembling agents and workflows. Evaluate them at that layer, then establish how the chosen workflow reaches each business operation.
Keep MCP, connectors, and orchestration distinct
MCP standardises tool discovery and invocation. A tool can invoke a single request or a substantial workflow. Its implementation determines what happens inside the application.
Connectors provide application operations. RPA supplies software robots for defined tasks. Orchestration coordinates steps, state, approvals, and failures. A product can combine these responsibilities, and a workflow can use several products.
For your support escalation, record which component owns the service request and which confirms the final CRM update. If one succeeds and the other fails, someone needs to know what has already changed before retrying.
Run the same job through each proposed approach
Use the account that would run the production workflow. Include an ambiguous record, an approval, and a failure after an earlier step succeeds.
| Criterion | Evidence to ask for |
|---|---|
| Operation coverage | Each required read and write working on your objects, custom fields, and application version |
| Identity and controls | Execution identity, permission scope, approval checks, and revocation behaviour |
| Completion and recovery | Readback of the intended state; safe handling of partial completion and retries |
| Deployment | Where credentials, execution, model requests, and logs are handled |
| Maintenance | A named owner and a way to retest affected operations after application changes |
| Total effort and cost | Setup, extensions, usage, retries, maintenance, and human review |
If your existing platform completes the job with acceptable controls and effort, keep using it. If the unresolved work is discovering and operating deeper application behaviour, scope a Monarch pilot around those specific actions.
FAQ
Does a pre-built connector cover every feature in an application?
Check its supported operations, fields, and authentication. A required feature may need configuration, an extension, or another authorised access route.
Can an agent builder and an integration platform work together?
Yes. The builder can own the agent experience and reasoning while an integration platform supplies executable tools. Assign ownership for identity, approvals, workflow state, and recovery across that boundary.