This checklist pulls together the controls that matter most for teams running MCP servers or giving AI agents access to tools and APIs, grouped by the stage where each control actually gets applied. It's not a substitute for the deeper guidance elsewhere in this series, but it works as a review tool before connecting a new server, launching a new agent, or auditing what's already in production. Go through each group in order. Identity and access come first because nothing else here matters if a caller was never verified in the first place, and supply chain review comes last because it's the check most teams forget to repeat once a server's already been running quietly for months.

Identity and access control

  1. Confirm every MCP server requires real authentication and never relies on network location alone. A server that trusts anything reachable on its network has no meaningful way to distinguish a legitimate client from one that shouldn't be there at all.
  2. Verify authorization happens on every individual tool call, not just once at connection time. Authenticating a client tells you who's connected; it says nothing about whether that specific call, with those specific parameters, should actually be allowed.
  3. Apply least privilege to every credential, scoping each server and tool to the minimum access its job requires. A tool that only reads one table doesn't need a credential capable of writing to the whole schema.
  4. Use an allow-list default for new tools and servers, requiring deliberate approval before anything becomes reachable. This fails safe: an oversight leaves a tool unavailable rather than silently reachable.
  5. Distinguish user identity from service identity clearly in every authorization decision. A tool's permission check should generally evaluate the actual requesting user, not the broader access of the service technically making the call.

Input, output, and parameter integrity

  1. Validate every tool parameter's type, format, and range before it executes, rejecting anything outside a defined schema. A model-supplied value deserves the same scrutiny you'd give input from an anonymous user.
  2. Treat data returned by tools as untrusted content, since it can carry injected instructions the same way any external input can. A document or message a tool fetches becomes part of the model's context the moment it's returned.
  3. Cross-check parameters against real, existing data rather than trusting a syntactically valid value on its own. A well-formed record identifier that doesn't belong to the requesting user is exactly the kind of manipulation static validation alone will miss.
  4. Enforce business-rule limits, like spending caps and approved recipients, as hard rules outside the model's own reasoning. A manipulated model can be talked out of a soft instruction; it can't argue past a limit enforced at the tool boundary.
  5. Sanitize error messages so they never leak internal details, stack traces, or information that confirms or denies the existence of records the caller shouldn't see. Errors flow into the model's context the same as any other tool output.

Containment and operational controls

  1. Sandbox execution for tools that run code or process untrusted files, so a bad call stays contained to an isolated environment. Sandboxing doesn't prevent a bad call, it limits what that call can reach once it happens.
  2. Rate limit tool calls per identity, with tighter limits on higher-impact tools than on simple read-only ones. Most runaway tool usage comes from an agent stuck in a loop, not a deliberate attack, and a limit catches both.
  3. Constrain outbound destinations for messaging, email, and API tools to a known, approved set wherever the use case allows it. An arbitrary destination parameter gives a manipulated call far more reach than a constrained one.
  4. Require human approval for high-impact or irreversible actions, enforced independently of the model's own judgment. Anything that can't be easily undone deserves a check that doesn't depend on the model recognizing its own risk.
  5. Set resource and cost limits that apply regardless of how legitimate an individual call sequence appears. A sequence of individually reasonable calls can still add up to a cost or exposure problem nobody approved.

Visibility and ongoing review

  1. Log every tool call, including identity, parameters, results, and policy decisions, not a sample of them. A partial log turns an investigation into a guessing exercise about the gaps.
  2. Protect tool call logs with access controls matching the sensitivity of the data they contain. An audit trail of tool activity often holds the same sensitive data the tools themselves handle.
  3. Monitor for unusual volume, unusual sequences, and repeated denials, not just individual call failures. A single call can look fine in isolation while still being part of a pattern worth flagging.
  4. Re-test authentication, authorization, and validation after any update to a tool's schema or a server's version. A control that held up against last month's schema doesn't automatically hold up against this month's.
  5. Review third-party MCP servers on a recurring basis, not only at initial adoption, since behavior can change with an update nobody flagged. A server that passed review once isn't guaranteed to still deserve that trust after several silent updates.

Incident readiness

  1. Define in advance which credentials get revoked first and who has the authority to revoke them. Deciding this during an active incident costs time you don't have.
  2. Know whether sent messages, executed transactions, or written records can be reversed, and how, before you need to reverse one under pressure.
  3. Practice at least one tabletop exercise around a suspected tool compromise or data exfiltration attempt, so the response plan gets tested somewhere other than a real incident.

Where TELEON fits

TELEON is built to sit at the tool-call boundary as a gateway, applying policy enforcement, recording an audit trail, and supporting privacy vault tokenization across MCP servers and tool integrations regardless of which framework or model provider is behind them. That gives teams a consistent way to apply several of the controls above, particularly identity and access enforcement, logging, and monitoring, across a set of tools that were each likely built with different levels of security rigor.

TELEON doesn't replace the work of hardening an individual server's internal authentication, defining the right validation schema for a specific tool, or reviewing a third-party server's code before connecting it. Those remain decisions and engineering work that sit with the team building or adopting each integration, and this checklist is meant to help make sure none of them get skipped simply because they weren't on anyone's list.

A checklist like this one is most useful the first time a team runs through it deliberately, and least useful the moment it turns into a box-checking exercise nobody actually revisits. The real value comes from treating each item as a live question to re-ask whenever something in the environment changes, a new tool, a new server, a new model version, rather than a one-time gate a project passed through on its way to production.