Agentic Index

Klavis AI vs Paragon (2026)

Both vendors last verified

Klavis is MCP infrastructure in the purest sense, with hosted production MCP servers and built in OAuth across more than a hundred apps, plus the open source Strata server you can run yourself, free to start. That verdict is the Agentic Index coverage score, graded from each vendor's own published materials.

Paragon is a managed integration platform that speaks MCP among other things, with hundreds of agent actions, triggers, RAG sync and workflows. This is a bet on protocol against platform. Choose Klavis if you are building on MCP and want to own the servers. Choose Paragon if you want the integration problem handled.

On the Agentic Index agent infrastructure ranking, neither Klavis AI nor Paragon clears the bar, which asks for all five production contract capabilities documented in full. Klavis AI does not document security and identity governance in full, nor observability and auditability; Paragon does not document testing, debugging and optimization in full. 33 of the 186 vendors in the lane clear it. See the agent infrastructure ranking

This comparison is published by Agentic Index, an independent agentic AI vendor research platform. Klavis AI and Paragon are each graded against the same 14 capability Agentic Index taxonomy, from the vendor's own public materials under the Agentic Index verification standard, alongside 1,084 researched vendors. No vendor pays for placement and no vendor has reviewed this page. How this evidence is graded

Choose Klavis AI if

  • You have committed to MCP and want hosted servers plus an open source option you control.
  • Self hosting is a requirement, and the Strata server being open source is the reason you are looking.
  • A free tier that lets you run real workloads matters more than breadth of prebuilt actions.

Choose Paragon if

  • You want the integration problem solved rather than the protocol implemented well.
  • Triggers, RAG sync, workflows and observability are in scope.
  • An embedded integration experience for your own customers shortens your build.
Feature
K
Klavis AI
P
Paragon
Action & orchestration

Integrations & Tool Calling

Ability to connect agents to real systems through native integrations, OAuth-authenticated actions, custom tools, APIs, webhooks, or MCP-compatible tools.

Workflow Orchestration

Ability to sequence, branch, retry, route, and combine deterministic workflow nodes with autonomous agent steps.

Triggers & Channel Coverage

How agents wake up and where they work: schedules, webhooks, message events, CRM events, inbox events, chat, email, voice, and collaboration tools.

Knowledge & context

Knowledge Grounding & RAG

Ability to ground agent behavior in company data through document ingestion, retrieval, external knowledge APIs, semantic search, or RAG layers.

Memory & State Persistence

Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer.

Control & trust

Human Oversight & Guardrails

Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls.

Security, Identity & Governance

RBAC, SSO, auditability, encryption, least-privilege tool access, compliance posture, and data handling policy.

Observability & Auditability

Traces, logs, execution histories, metrics, audit events, and debugging detail for production agent behavior.

Deployment & Data Residency

Deployment modes and options, including SaaS, dedicated cloud, VPC, on-prem, hybrid, local runtime, and self-hosting.

Solution readiness

Prebuilt Agents, Templates & Packs

Ready-made workflows, packaged employees, templates, blueprints, industry solutions, and role-specific agents that reduce time-to-value.

Platform extensibility

Model Flexibility & Routing

Ability to work across multiple foundation models, route tasks to different models, or let buyers bring their own providers and keys.

APIs, SDKs & MCP Extensibility

Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems.

Testing, Debugging & Optimization

Testing, debugging, scoring, retries, fallbacks, quality gates, and optimization loops for improving agent workflows before and after deployment.

Specialist automation

Browser & Computer Use

Browser, desktop, or remote/local computer control for workflows that cannot be handled through stable APIs alone.

Pricing snapshot

Sourced from the Index pricing dataset · open each vendor's profile for full detail.

Pricing
K
Klavis AI
P
Paragon

Entry price

Lowest public entry point

Free (open source servers and a hosted free plan); Pro and Enterprise unpriced; sandboxes by quote Platform and Enterprise plans, priced by Connected Users; custom quote

Pricing confidence

How public the numbers are

Public, partial Contact only

Billing

Primary billing axis

not published (plan tiers named in the FAQ; sandbox environments by quote) Connected Users (customer tenants using integrations), with default usage built in per plan

Variable cost

Workload / overage exposure

Medium variable cost Medium variable cost

Free tier / trial

Try before you buy

Free tierTrial
Free tierTrial

Buying motion

Self-serve vs sales call

Mixed Mixed

Pricing verified

When this pricing was last checked

Product updates

Newest first, each linked to its source.

Paragon

  • · Deployment / data residency

    Paragon introduced Versioned Releases for its integration platform.

    Source
  • · Integrations

    Paragon launched Smart Rate Limits to manage and optimize API requests across its integration infrastructure.

    Source
  • · MCP / tool calling / API

    Paragon introduced its managed Model Context Protocol (MCP) server to connect AI products to over 130 third-party integrations.

    Source

Other matchups in agent infrastructure platforms

Not the pairing you were after? These compare a different set of agent infrastructure platforms on the same 14 capabilities.

See all 142 agent infrastructure platforms comparisons

Contact us

Found a vendor we missed? Have feedback on the index? We'd love to hear from you.