How to Debug AI Tool-Calling Loops
Debug invalid arguments, repeated tool calls, missing results, stuck multi-round loops, and provider-specific tool state with structured traces and deterministic limits.
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MCP
Model Context Protocol fundamentals, tools, permissions, function calling, and agent integrations.
29 articlesHow to Design Good AI Tool Schemas
Design tool names, descriptions, JSON schemas, enums, required fields, error contracts, and side-effect boundaries that models can use reliably and applications can validate safely.
Read articleHow to Execute Parallel AI Tool Calls Safely
Run independent model-requested tools concurrently without breaking dependencies, permissions, ordering, cancellation, idempotency, or deterministic result correlation.
Read articleFunction Calling vs Tool Calling vs Agents
Understand the difference between function calling, tool calling, and agents, and where execution loops, permissions, state, and autonomy actually belong.
Read articleHow to Handle Untrusted AI-Generated URLs
Safely handle URLs generated by models, tools, search results, and retrieved content using parsing, scheme restrictions, network-boundary checks, redirect policy, user confirmation, and SSRF-style defenses.
Read articleHosted Tools vs Client-Executed Tools
Compare provider-hosted tools with tools executed by your own AI client across state, privacy, portability, latency, authorization, and reliability.
Read articleHow to Build Human Approval Into AI Tool Calls
Design AI tool approvals that show exact operations, bind consent to normalized arguments, support per-tool policies, and remain safe across retries, crashes, and multi-round workflows.
Read articleIdempotency for AI Tool Execution
Prevent duplicate side effects in AI tool workflows using stable operation IDs, idempotency keys, durable execution records, recovery rules, and downstream API guarantees.
Read articleMCP Architecture Explained for App Developers
Understand the current Model Context Protocol architecture: clients, servers, tools, resources, prompts, transports, stateless requests, extensions, permissions, and application state.
Read articleHow to Build an MCP Client Permission System
Design per-server and per-tool MCP permissions with Ask, Always Allow, Disabled, argument-bound approval, revocation, persistence, audit history, and safe defaults.
Read articleMCP Elicitation Explained
Understand MCP elicitation in the modern stateless protocol: input-required results, client UX, validation, request state, privacy, approvals, cancellation, and multi-round workflows.
Read articleMCP Multi-Round-Trip Requests Explained
Understand MCP Multi Round-Trip Requests (MRTR): input_required, inputResponses, requestState, stateless retries, elicitation, cancellation, security, and recovery.
Read articleMCP Streamable HTTP Explained
Understand modern MCP Streamable HTTP: stateless requests, required headers, JSON-RPC bodies, subscriptions, routing, retries, authentication, and migration from older session-oriented transports.
Read articleMCP Tasks Explained
Understand the MCP Tasks extension for long-running work: task creation, tasks/get, tasks/update, cancellation, subscriptions, persistence, retries, and recovery.
Read articleHow MCP Tool Discovery Works
Understand MCP tool discovery, schema freshness, server identity, cache invalidation, capability changes, security boundaries, and how clients should expose discovered tools to models.
Read articleHow to Migrate MCP Clients Across Protocol Versions
Migrate MCP clients across protocol revisions with explicit capability profiles, modern stateless requests, MRTR, Tasks, subscriptions, OAuth hardening, deprecations, and compatibility tests.
Read articleHow Multi-Round AI Tool Loops Work
Build reliable model-tool-model loops with round limits, state, context, tool results, cancellation, recovery, cost budgets, and deterministic stopping conditions.
Read articleHow to Prevent Prompt Injection From Tool Results
Treat tool output as untrusted data, preserve provenance, enforce authorization outside the model, and contain prompt injection in tool-using AI systems.
Read articlePrompt Injection vs Tool Authorization
Understand why prompt-injection defenses and tool authorization solve different problems, and how to keep model-controlled text from becoming permission to perform real-world actions.
Read articleHow to Secure Remote MCP Servers
Secure remote MCP servers with OAuth, issuer and audience checks, resource indicators, scopes, transport security, tool authorization, prompt-injection defenses, and auditable client policy.
Read articleHow to Test an MCP Client
Build deterministic MCP client tests with fake servers, protocol fixtures, malformed payloads, permissions, MRTR, Tasks, subscriptions, OAuth failures, and version compatibility.
Read articleHow to Validate AI Tool Arguments Safely
Validate model-generated tool arguments through parsing, schema checks, normalization, authorization, business rules, previews, and bounded execution before any side effect.
Read articleHow AI Tool Calling Works: From Model Decision to Tool Result
Understand the full AI tool-calling loop: schemas, model-generated arguments, validation, execution, results, retries, parallel calls, and failure recovery.
Read articleHow MCP Tool Permissions Work: Ask, Allow, and Deny
A deep guide to MCP tool permissions, user approval, server authorization, tool arguments, trust boundaries, and safer Ask, Allow, and Disabled policies in AI clients.
Read articleHow Interactive MCP Workflows Work: MRTR, Elicitation, Tasks, and Stateless Servers
Understand MCP 2026-07-28 interactive workflows: stateless requests, Multi Round-Trip Requests, elicitation, explicit state handles, and the Tasks extension.
Read articleOAuth for MCP Explained: How Secure MCP Authorization Works
Understand MCP authorization with OAuth 2.1, PKCE, resource metadata, issuer validation, resource indicators, credential isolation, and client registration.
Read articleMCP Security Checklist: What to Check Before Connecting a Server
A practical MCP security checklist for clients and users: server identity, OAuth, tool permissions, argument review, prompt injection, data exfiltration, retries, and revocation.
Read articleMCP Tools vs Function Calling: What Is the Difference?
Understand how MCP tools differ from model function calling, how they fit together, what each layer controls, and why the distinction matters for security.
Read articleWhat Is MCP and Why Does It Matter for AI Apps?
Learn what the Model Context Protocol is, how MCP tools fit into an AI chat workflow, and why permissions and server trust matter.
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