MCP Manager Features Page

Works with Anthropic, OpenAI, and all MCP-compatible environments.

Flexible deployment options for different org needs.

Spin up gateways for dev, staging, or production easily.

Scale without worrying about limits or concurrency issues.

Secure endpoints and keys are automatically generated.

View and manage all connected servers from one dashboard.

Logs prompts, resources, tools, and 20+ additional metadata fields.

Token count per user, token count over time, feature calls, server popularity, error rates, and more.

Integrate metrics with existing observability stacks.

Detect usage spikes or suspicious activity across servers.

Receive alerts when users request new gateway access.

Get notified when new tools are added to your servers.

Monitor sensitive data or policy violations in real time.

Stay aware of broken connections or downtime instantly.

Every server must use secure, standards-based authentication.

Automates identity onboarding for new servers.

Eliminates stale credentials and minimizes risk.

Use shared credentials or per-user logins depending on policy.

Full control over what agents can access.

Reduce token usage, context overload, and operating costs.

Block tools if name, title, or description changes post-approval.

Assign fine-grained control to specific admins.

Blocks malicious prompt content before it reaches the agent or server. Prevents data exfiltration.

Detects and halts when a connected server or tool changes behavior after initial approval.

Prevents modified or malicious tools from being served to agents.

Stops attackers from creating duplicate or look-alike servers that impersonate trusted ones.

Flags and optionally suspends tools or users that deviate from expected call patterns.

Authenticates each server connection using signed tokens and verifiable origins.

Prevents one server from secretly invoking another server’s tools without authorization.

Detects and blocks sensitive patterns in MCP messages (e.g., phone numbers, SSNs, API keys, internal project IDs) via customizable regex rules with enforcement actions.
Detection: Pattern recognition via regular expressions.

Adds pre-trained PII detection and anonymization for broader entity coverage (e.g., names, addresses, financial data, and other personal identifiers).
Detection: NLP-based entity detection.

Connect internal DLP systems or third-party review workflows to inspect or approve messages before transmission.
Detection: API / external policy integration.