# Credal Build and govern enterprise AI agents and MCP servers with shared business context. - Findings24: - Website: - Pricing: Freemium - Categories: AI Agent Builder, AI Agent Infrastructure, MCP Tools ## What is Credal? Credal is an enterprise platform for building, deploying, and governing AI agents and Model Context Protocol (MCP) servers. It connects company systems and lets domain experts assemble the data, tools, and business instructions each team needs. Its MCP Platform acts as a gateway between agents and business systems, while Agent Builder supports visual and programmatic agent creation. Platform teams manage access, deployments, and usage centrally; employees use the resulting agents and servers through Claude, ChatGPT, Cursor, Slack, or custom applications. ## What can Credal do? ### Scoped MCP servers Compose department-specific servers from selected tools and actions. Enforce tool parameters to limit the records agents read and the actions they can take. ### Source permissions and action controls Inherit and sync source permissions, enforcing document access at query time. Restrict tools by user, group, or caller agent, and require human approval for sensitive writes. ### Visual and API agent creation Assemble instructions, knowledge, tools, and guardrails in a no-code canvas, then test in a live sandbox. Technical teams can create agents and update configurations through an API. ### Governed registry Publish shared agents and MCP servers with version control, rollback, domain ownership, and audit trails for actions and tool calls. ### Cost and accuracy optimization Attribute token spending to teams, workflows, and models. Evaluate cheaper models against workflow accuracy and route workloads to selected models. ### Consolidated audit logging Collect data-access and usage logs across agent surfaces. Export logs to a SIEM through native Splunk integration and OpenTelemetry support. ## Use Cases ### Revenue operations analysis Combine Salesforce opportunities, Snowflake queries, and Slack updates in a server that applies the team's revenue definitions and regional query constraints. ### Customer support workflows Build a support copilot using Zendesk, Confluence, and Google Drive knowledge, with case creation, escalation, and approval requirements for refund actions. ### Engineering context access Expose selected Jira, Confluence, and Snowflake tools to engineering agents in Cursor so developers can consult project information within their coding workflow. ### Employee policy assistance Assemble an HR policy server from Notion, Google Drive, and Slack, giving employees a way to query internal guidance through Slack. ## Frequently Asked Questions ### How is Credal priced? Enterprise pricing is custom and accounts for builder seats, user seats, data indexing, and model token usage. Teams contact sales to scope a plan. ### What deployment options are available? Credal supports multi-tenant cloud hosting, single-tenant cloud, and fully on-premises deployment. ### Can teams use their own AI models? Yes. Teams can connect Azure OpenAI deployments or self-hosted open-source models, or use Credal's managed access to models from OpenAI, Anthropic, and other providers. ### How does onboarding work? Credal offers time-boxed pilots with agreed success criteria and onboarding support. It reports that initial setup can take days, while enterprise rollouts with SSO and custom workflows typically take a few weeks, depending on scope. ## Quick Facts - **Product category**: Enterprise AI agent and MCP governance platform - **Integrations**: 1,000+ connectors, including Salesforce, Snowflake, Jira, Confluence, and Google Drive - **Identity management**: SSO, SAML, and SCIM included in every plan - **Security certification**: SOC 2 Type II - **Website**: https://credal.ai