Input validation for MCP tools means checking every parameter a model supplies before that parameter reaches the underlying system, treating it with the same suspicion you'd apply to input from an anonymous internet user. A model deciding to call a tool isn't a trusted decision the way a developer-written function call is. It's a value produced by a probabilistic system that can be manipulated by prompt injection, misled by ambiguous instructions, or simply wrong in ways that have nothing to do with malice. If a tool executes whatever the model hands it without checking it first, every one of those failure modes turns directly into an action against a real system.
Type and format checks are the baseline, not the whole job
Confirming a parameter is actually a number where a number is expected, or a valid date format, or a string within an expected length, is the minimum bar. It catches obvious model mistakes, but it won't catch a syntactically valid value that's semantically dangerous, like a well-formed but unauthorized record identifier, or a path string that happens to be correctly formatted but points somewhere it shouldn't.
Reject open-ended parameters wherever a narrower option exists
A tool parameter defined as "any file path" or "any SQL fragment" gives a model, and by extension anyone who can influence the model's behavior, far more reach than a parameter constrained to an enum of allowed values or a specific, bounded set of operations. Design tool schemas to be as narrow as the underlying task allows, since a narrower schema is validated almost automatically just by rejecting anything outside its defined shape.
Watch for injected instructions hiding inside otherwise valid parameters
A parameter can pass every type and format check while still containing text crafted to manipulate a downstream system, a query, a template, a shell command, that interprets that string as more than plain data. Validate not just the shape of a parameter but, where relevant, whether its content matches what a legitimate value for that field should actually look like.
Validate against business rules, not just data types
A transfer amount that's a syntactically valid number can still violate a business rule, like exceeding an account's actual balance or a user's approved limit. Input validation for MCP tools needs to include these business-level checks, not stop at the technical type check, because a technically valid but business-invalid parameter is often exactly what an attacker or a confused model produces.
Fail with a clear rejection, not a silent adjustment
When a parameter fails validation, reject the call outright rather than quietly clamping it to a nearby valid value or silently dropping the offending part. A silent correction can mask what actually happened and make the model, or an attacker probing the system, believe the original request succeeded as intended.
Combine validation with narrowly designed tool schemas
Input validation works best when it's paired with a schema that was designed to be validated easily in the first place, rather than bolted onto a tool that was originally built with wide-open parameters for convenience. A tool schema built around a small number of well-defined operations, each with a limited parameter set, makes strict validation almost automatic. A tool schema built around one flexible, catch-all parameter makes strict validation an ongoing fight against whatever creative input a model, or someone manipulating it, eventually generates.
Validate consistently across every tool, not just the risky-looking ones
It's tempting to focus validation effort on the tools that obviously touch sensitive data or high-impact actions, and let simpler-looking tools slide with looser checks because a mistake there seems less consequential. That gap is exactly where inconsistent validation tends to get exploited, since a chain of tool calls can route through a lightly validated tool specifically because it's the weakest link, even if the end goal involves data or actions that live somewhere else entirely.
Where TELEON fits
TELEON can apply policy checks against tool call parameters at the gateway, giving teams a place to enforce validation rules consistently across MCP servers and tools that might otherwise implement input handling with varying rigor.
Defining the actual validation rules, the allowed value ranges, the business constraints specific to each tool, still requires domain knowledge only the team that owns that tool has. A gateway can enforce a rule; it can't invent the correct one for you.
A short checklist
- Validate the type, format, and length of every parameter before a tool call executes.
- Prefer narrow, enumerated parameter schemas over open-ended free text wherever possible.
- Check parameter content for injected instructions, not just structural validity.
- Apply business-rule checks, like limits and balances, alongside technical validation.
- Reject invalid calls outright instead of silently correcting or clamping bad values.
- Log rejected calls, since a pattern of rejections can indicate probing or a misbehaving integration.
- Re-review validation rules whenever a tool's parameters or downstream system change.
Input validation for MCP tools isn't fundamentally different from validating input to any other API. What's different is the source: a model producing that input can be steered by content it read moments earlier, which means the validation layer is sometimes the only thing standing between a manipulated conversation and a real action, and it's worth treating it with exactly that level of seriousness.