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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteTool poisoning on MCP servers is an indirect prompt-injection attack: malicious instructions are placed in tool metadata—such as a description or parameter schema—and may influence an AI agent that reads it. The risk is real, but it does not mean every MCP server is malicious or that every model will follow the instructions. Treat tool metadata as part of the agent’s attack surface, inspect it before use, and limit what the agent can do at runtime.
What tool poisoning means
OWASP defines MCP tool poisoning as an indirect prompt-injection attack against AI agents connected to external tool servers through the Model Context Protocol (MCP). Microsoft likewise describes malicious instructions embedded in MCP tool descriptions. OWASP’s broader guidance also flags parameter schemas and tool return values as inputs that can carry risky content. OWASP’s MCP Security Cheat Sheet and its MCP Tool Poisoning guidance distinguish this attack surface from an ordinary instruction typed by the user: the agent may encounter the instruction while interpreting a tool or its output. Microsoft’s 2025 explanation discusses this metadata-based attack path.
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A tool description is not merely documentation for a person. It helps an MCP client or agent understand what a tool does and when it might be useful. A malicious or misleading description can therefore try to influence tool selection or the agent’s behavior. The exact way metadata is presented and handled varies by client; not every MCP implementation works identically.
How an attack can reach an agent
- A server offers a tool. The agent receives a name, description, and parameter schema, and may later receive the tool’s output.
- Instructions are embedded in the tool interface. A description or schema might include directions that go beyond explaining the tool’s legitimate function.
- The agent interprets that content. Depending on the client and model, the text may affect which tool the agent selects or what it attempts to do next.
- The agent may act using its existing access. If it has permission to read data or invoke other tools, a poisoned instruction may try to exploit that access—for example, by steering it to request sensitive context or pass data through an action.
The 2026 ACM survey of MCP security notes that many clients use textual names and descriptions without cryptographic verification or contextual awareness, and discusses self-promoting directives that may influence tool preference. This describes a design concern, not a guarantee about every client or a measured rate of successful attacks. The survey record provides that broader context.
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What tool poisoning can—and cannot—establish
A poisoned tool interface can attempt to get an agent to follow hidden instructions, favor an attacker-controlled tool, request sensitive information, or take an action that moves data. Whether any attempt succeeds depends on the client’s behavior, the model, the tool implementation, the agent’s permissions, and the surrounding environment. Metadata alone does not prove that a system was compromised.
Tool poisoning is also not the same as indirect prompt injection through tool results. In the latter case, the risky instruction arrives in content returned by a tool or another external source; in tool poisoning, it is embedded in the tool interface itself. OWASP also discusses adjacent MCP risks such as tool shadowing and server-side request forgery (SSRF). Those are related security concerns, not interchangeable names for tool poisoning.
There is no representative prevalence figure established here for how many MCP servers are poisoned or how often attacks succeed. Nor does the phrase “nobody’s patching” establish that every implementation lacks safeguards. Anthropic’s current agent-threats guide defines tool poisoning as compromise of tool interfaces such as MCP descriptors, schemas, or metadata, but a category definition does not quantify incidence or prove that a universal patch exists. Anthropic’s agent threats guide is useful for that distinction. Available mitigations include policy, metadata review, and runtime controls; no cited source establishes one complete prevention method.
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Reduce exposure before connecting a tool
Inspect descriptions and schemas
Review the exact metadata the agent will receive, not just a server’s marketing description or a tool’s name. Check whether the description explains a narrow, legitimate function and whether the schema requests only the inputs needed for that function. Treat unexpected instructions—especially directions unrelated to the stated task—as a reason to investigate before making the tool available.
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Anthropic’s MCP Directory Policy states: “MCP tool descriptions must narrowly and unambiguously describe what the tool does and when they should be invoked.” That is a directory requirement and a useful authoring standard; clear wording by itself does not prove a tool is safe. Read the MCP Directory Policy.
Scan metadata before exposing tools to the agent
A control plane can inspect descriptions for hidden instructions, typosquatting, and adversarial patterns before the tool is offered to the model. Microsoft describes this as a pre-use control in its 2026 article on securing MCP tool execution. A scan can help flag suspicious metadata, but it should not replace human review or authorization checks. Microsoft’s control-plane overview.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Constrain tool use at runtime
Pre-use review and runtime validation address different moments in the attack path. A review examines what the model is being shown; runtime controls examine the calls and responses that follow. Validate tool calls against expected schemas and policy, inspect responses where appropriate, and require authorization for actions that could expose sensitive data or cause consequential changes. Keep an agent’s permissions limited to the task, rather than assuming that a trustworthy-looking description makes broad access safe.
The 2026 ShieldMCP paper in the Association for Computational Linguistics Anthology reports results from its own red-team evaluation across five LLM backends: attack success rates fell from 74% to under 9% for tool poisoning and from 47% to under 6% for indirect prompt injection through tool responses, with median added latency below 120 ms per tool call. These are paper-specific evaluation results, not a production guarantee or a universal benchmark for MCP deployments. Read the ShieldMCP paper.
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Match controls to the attack path
| Question | Tool poisoning | Indirect prompt injection through results | Useful control layer |
|---|---|---|---|
| Where does the instruction enter? | Tool metadata, such as a description or schema | Content returned by a tool or external source | Inspect metadata before exposure; validate calls and responses at runtime |
| When can a control act? | Before the tool is offered to the model, and during later call handling | When returned content is processed and during subsequent actions | Use both pre-use review and runtime checks |
| What trust should not be assumed? | That server identity or publisher reputation makes its instructions safe | That external content is trustworthy because it came through a connected tool | Inspect behavior and enforce explicit, constrained authorization |
These distinctions help avoid relying on a single safeguard. Identity and reputation can inform a decision, but neither substitutes for reviewing what an agent will consume or limiting what it is authorized to do.
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