inputSchema
inputSchema is the JSON Schema object describing a tool's arguments. It tells the client what parameters exist, their types, and which are required, so a model can construct a valid call without a human writing an integration. It is required on every tool and was present on all 288 tools we read.
What is inputSchema?
inputSchema is a JSON Schema object attached to each tool, describing the arguments that tool accepts. It names the properties, gives each one a type, and lists which are required.
This is what lets a model call a function it has never seen before. The schema is the contract.
Why is it the field that matters most?
Because it is the only structural guarantee in the response. The description tells a model what a tool is for in prose, which can be vague; the schema tells it exactly what shape the call must take, which cannot.
It is also the field with no fallback. A missing description makes a tool hard to choose. A missing or wrong inputSchema makes it impossible to call correctly.
How consistently do servers provide it?
Universally, in our sample. All 288 tools returned by 14 servers on 5 August 2026 carried an inputSchema, the same 100% coverage name and description had.
That is the strongest consistency finding in the corpus, and it is what makes MCP usable in practice: a client can rely on the schema being there and validate against it, rather than probing.
Example
A search tool's inputSchema typically declares a single required string:
{"type": "object", "properties": {"query": {"type": "string"}}, "required": ["query"]}
A model reading that knows it must send an object with a query string and nothing else is mandatory. https://mcp.exa.ai/mcp returned 2 tools on 5 August 2026, each with a schema of exactly this kind, which is enough for a client to call them without any hand-written integration code.