Klavis AI vs Metorial (2026)

Hosted MCP servers from Klavis cover more than a hundred applications, from Affinity and Airtable to Zendesk and Zoho Mail. Each one connects per end user through OAuth 2.0 or an API key, so an agent reads and writes in that user's own accounts. Tools are reached through each server's MCP URL, through Strata or through the Call Tool API for plain function calling. Strata is one MCP server that lets the agent discover categories and actions across every connected server before executing one.

Sourceklavis.ai/docs/mcp-server/overviewread 2026-09-22

More than 1,000 catalog integrations are available, each deployed as a provider with its own config and per user authentication (OAuth through Provider Setup Sessions, API tokens or custom credentials). Their tools reach the agent through a session's MCP URL or direct tool calls on the API. Customers add their own tools as custom providers deployed from code, container images or remote MCP servers, and can use their own OAuth apps.

Sourcemetorial.com/docs/build/operate/providersread 2026-09-22

The product executes the tool calls an agent makes and returns the results. Sequencing, branching and handoff live in the customer's own framework, and Klavis publishes guides for LangChain and LangGraph, LlamaIndex, CrewAI, Agno, Mastra, Google ADK and the major model APIs. Strata's discover, browse and execute tools help the agent pick an action. Klavis has no workflow runtime of its own to sequence, branch, retry or route work, or to combine deterministic workflow nodes with autonomous agent steps.

Sourceklavis.ai/docs/ai-platform-integration/overviewread 2026-09-22

Agents connect to tools through Metorial, which does not run the agent itself. Sessions merge the tools of several providers behind one connection. Magic Skills package instructions, files and optional scripts that the customer's AI client or agent follows when it invokes the skill. Sequencing and branching happen in that client or in the customer's framework, and Metorial has no workflow runtime of its own.

Sourcemetorial.com/docs/platform/workforce/magic-skillsread 2026-09-22

Slack and Discord clients come alongside the hosted servers, so a person can put MCP tools to work from those chat channels. Klavis gives no setup guide for either client. It names no schedule, webhook, event subscription or inbound queue that starts work without a person asking.

Sourceklavis.ai/faqread 2026-09-22

Providers expose triggers that fire on events in the external system. A callback, which is a webhook Metorial registers against every matching integration instance, notifies the customer's application so it can run event driven workflows. Callbacks are a metered plan feature, with 10,000 a month on Dev and 100,000 on Scale.

Sourcemetorial.com/docs/build/glossaryread 2026-09-22

MCP servers for Notion, Google Drive, Confluence and similar tools let an agent query those systems live, but Klavis builds no retrieval layer over the customer's own content. Strata finds tools, not documents, by browsing categories and actions instead of semantic search. Klavis names no ingestion, indexing, retrieval or RAG layer of its own, so there are no retrieved passages or sources to show.

Sourceklavis.ai/docs/concepts/strataread 2026-09-22

Agents get live access, through Metorial's integrations, to the systems that hold company knowledge, such as Google Drive, Notion and Confluence. A Magic Skill can carry reference documents for its instructions. There is no index, retrieval layer or semantic search over the customer's corpus. The API has Documents and Stores resources, but Metorial does not present them as retrieval.

Sourcemetorial.com/docs/platform/get-started/core-conceptsread 2026-09-22

Each end user's credentials and integration status are stored so tools act without asking for consent again. A sandbox holds application state for one training or evaluation run. Klavis names no memory layer that keeps an agent's context across runs. Its Mem0 server connects an agent to another vendor's memory product.

Sourceklavis.ai/docs/api-reference/user/get-user-integrationsread 2026-09-22

Sessions are lightweight runtime contexts created per request or per user interaction. Metorial stores each user's provider credentials as auth configs for reuse. There is no memory layer that keeps an agent's context across runs.

Sourcemetorial.com/docs/build/operate/sessionsread 2026-09-22

Each end user authorizes an integration through OAuth consent before its tools act, and a server connection can be set read only through the API. Klavis Guardrails sits as a proxy between MCP clients and servers. It detects tool poisoning and prompt injection, enforces least privilege access and checks tool invocations against allowlists. Klavis names no approval step a person acts on before an action commits, whether at a node, workflow or policy layer.

Sourceklavis.ai/docs/enterprise-security/klavis-securityread 2026-09-22

Several controls constrain what agents may do. Access groups decide which integrations and skills each user or SSO group sees. People request more access, and administrators review and resolve those requests. Session tool filters can restrict a provider to read only tools, and Protoguard screens each message and tool call, blocking prompt injection and requests outside the customer's policies. No person approves a specific agent action before it commits.

Sourcemetorial.com/docs/platform/workforce/portalsread 2026-09-22

The API enforces HTTPS with API key authentication. Each end user's credentials are scoped per integration and returned only to the key owner that controls the instance, and customers can run OAuth through their own white label OAuth apps. Connections can be set read only, and Klavis Guardrails enforces least privilege tool access. No attestation or certification is published. On security, Klavis points only to its built in OAuth, and it publishes terms, privacy and cookie policies but no trust center. Klavis names no SSO, roles or audit trail.

Sourceklavis.ai/docs/api-reference/overviewread 2026-09-22

The platform is SOC 2 Type 2 compliant, independently audited for security, availability and confidentiality, with reports under NDA. It is also GDPR compliant, with a DPA and a published subprocessor list, and Metorial displays a SOC 2 badge on its homepage. Access uses SSO and SAML with per user and per group policies, and roles are named permission sets attached to members and teams. SCIM and SAML IdP sign in are offered too, and secrets are encrypted in Vault with keys managed through KMS. RBAC and SAML SSO come with the Enterprise plan.

Sourcemetorial.com/securityread 2026-09-22

The API returns server instances, tools, users and authentication status, and users check authentication in the dashboard. Klavis names no log, trace, execution history or audit event of the tool calls an agent makes through it, and no export to a SIEM. Guardrails' real time threat detection acts on calls as they happen, and Klavis does not say whether it keeps a record the customer can inspect.

Sourceklavis.ai/docs/api-reference/overviewread 2026-09-22

Connection logs record what agents did. Each session has a timeline, and every tool call opens to its tool name, arguments and result. Logs filter across sessions by status, source and agent, with tool errors listed separately. Workforce shows each agent's operations and connection history tied to its linked identity. The logs also carry provider auth and Protoguard events, and the Tool Calls API exposes inputs, outputs and status. Log retention is 30 days on Dev, 90 on Scale and custom on Enterprise.

Sourcemetorial.com/docs/platform/integrations/review-connection-logsread 2026-09-22

Hosted servers run on Klavis's infrastructure with a stated 99.9% uptime SLA. There are two production servers, api.klavis.ai for the US and api.eu.klavis.ai for the EU. For on premises or custom deployments, every MCP server ships as a Docker image to run in the customer's own infrastructure, and Strata is open source. Customers can pick the US or EU region, or run the servers in their own environment.

Sourceklavis.ai/docs/concepts/mcpread 2026-09-22

Deployment can sit in Metorial's cloud or the customer's. On premises deployment runs in the customer's own cloud or data center, and customers can choose EU or US regions for data residency. Each provider runs in its own isolated enclave behind firewalls. On premises deployment comes with the Enterprise plan.

Sourcemetorial.com/securityread 2026-09-22

The catalog holds MCP servers and tools. They give an agent actions to take and do no work on their own when selected. The framework guides build example agents as tutorial code. Klavis names no ready made workflow, template or role specific agent of its own for a customer to adopt.

Sourceklavis.ai/docs/mcp-server/overviewread 2026-09-22

Metorial supplies the tools to package a customer's own workflows. Magic Skills come with templates, groups and curated skill marketplaces, imports from public repositories, and portals that publish them to users. The skills in those catalogs are written by the customer's own experts. The integration catalog is a set of integrations, and the three sample apps in the docs are tutorial code. Metorial ships no ready made skill, template or role specific agent of its own.

Sourcemetorial.com/docs/platform/workforce/magic-skillsread 2026-09-22

Tools are served to whatever model the customer runs. The List Tools API returns a server's tools in several model formats, and integration guides cover OpenAI, Anthropic's Claude, Gemini, Mistral, Cohere, Together AI and Fireworks AI, each using the customer's own provider key. Klavis names no model of its own, so the model, the provider and the key are the customer's throughout.

Sourceklavis.ai/docs/ai-platform-integration/overviewread 2026-09-22

Tools reach whatever model the customer runs. The provider runtime formats session tools for OpenAI, Anthropic, Google Gemini and OpenAI compatible APIs such as DeepSeek, Together AI and xAI, and for the Vercel AI SDK, each called with the customer's own provider key. Any MCP client, such as Cursor, Claude Code or Codex, can connect. Metorial names no model of its own, so the model, provider and key are always the customer's choice.

Sourcemetorial.com/docs/build/providersread 2026-09-22

Outside callers reach Klavis through a REST API at api.klavis.ai with a published OpenAPI specification. Python and TypeScript SDKs cover servers, Strata, users, OAuth, white labeling and sandboxes. Klavis serves MCP as an addressed service, with each hosted server and each Strata instance at its own URL. The servers and Strata are open source for self hosting.

Sourceklavis.ai/docs/installationread 2026-09-22

A REST API with keys scoped to one environment makes Metorial callable from outside. It covers providers, deployments, sessions, tool calls, skills, portals and callbacks, alongside JavaScript and Python SDKs and a CLI. Metorial serves MCP as addressed endpoints, a session connection URL and Magic MCP URLs. Customers package their own tools as versioned custom providers with rollback.

Sourcemetorial.com/docs/build/apiread 2026-09-22

Isolated sandboxes of real applications let the customer test and train its agent. A Klavis Sandbox is loaded with a deterministic world state, and the agent works against it through MCP. The full state can be exported to compare against ground truth, and the sandbox resets for the next run. The Universe API acquires benchmark task environments, and its verify endpoint runs the task's check and returns whether the task passed, with the failure reason. Sandboxes can also be configured for the MCP-Atlas, Toolathlon and MCP-Mark benchmarks.

Sourceklavis.ai/docs/api-reference/universe/verify-taskread 2026-09-22

Customers can test before production. Sandbox environments have their own deployments, keys, auth configs and logs, and a development key never reaches production. Metorial Explorer calls a provider's tools against test data, and custom providers have version pinning and instant rollback. There is no way to evaluate the customer's agent with a readable, comparable result such as scored test cases, a pass rate or a judge verdict.

Sourcemetorial.com/docs/build/operate/organizations-and-projectsread 2026-09-22

The Local Sandbox API starts a virtual machine hosting interconnected MCP servers, among them Playwright for a browser plus a terminal and Desktop Commander for the machine. It serves filesystem, terminal, browser and document workflows during agent training and evaluation. Klavis restricts it to use outside production and says nothing more about driving a browser through the hosted Playwright server. The hosted MCP servers and Strata work through application APIs, not interfaces.

Sourceklavis.ai/docs/api-reference/local-sandbox/acquireread 2026-09-22

Everything runs through APIs and MCP servers, which is how Metorial's providers reach applications. Metorial has no browser, desktop or remote machine control of its own.

Sourcemetorial.com/docs/build/operate/providersread 2026-09-22