ChatGPT integration guideChatGPT 集成指南

Best APIs to Use with ChatGPT for AI Workflows适合 ChatGPT AI 工作流的最佳 API

The best API supplies a capability ChatGPT does not own—current evidence, private knowledge, or a controlled action—through a narrow contract your application or workspace can govern.真正适合 ChatGPT 的 API，应补足模型本身不具备的能力：最新证据、私有知识或可控操作，并通过应用或工作区能够治理的窄接口接入。

Short answer: start with web search for current evidence, GitHub for software work, Slack or Notion for team context, Stripe for controlled commerce, and Twilio for communications. In ChatGPT, use Apps or a GPT Action; in an OpenAI API product, use tool calling or MCP. Pilot one read-only workflow before enabling writes.简要结论：最新事实从网页搜索开始，研发协作选 GitHub，团队知识选 Slack 或 Notion，交易选 Stripe，消息触达选 Twilio。在 ChatGPT 内使用 Apps 或 GPT Action；在基于 OpenAI API 构建的产品中使用工具调用或 MCP。先试点一个只读流程，再开放写操作。

Compare the API shortlist比较候选 API Test a ChatGPT workflow in QVeris在 QVeris 测试 ChatGPT 工作流

ChatGPT workflow routing controlled requests through an orchestration gateway to six external API capabilities

Selection principle选择原则

Choose capabilities, not a pile of integrations按能力组合，而不是堆积集成

There are two distinct integration surfaces. Inside ChatGPT, Apps connect approved services and GPT Actions connect a custom GPT to APIs described with OpenAPI. In a developer-built application, OpenAI tool calling lets the model propose a function and arguments while your application validates and executes the call. Keep credentials, authorization, and consequential execution outside model judgment.这里有两种不同接入面：在 ChatGPT 内，Apps 用于连接获准服务，GPT Actions 则让自定义 GPT 通过 OpenAPI Schema 调用外部 API；在开发者自建应用中，OpenAI 工具调用由模型提出函数与参数，再由应用校验并执行。凭据、授权和高影响执行都不能交给模型判断。

01 · FIT

Task fit任务匹配

Prefer an API that returns the smallest authoritative object needed for the decision. A broad endpoint that dumps pages of text creates more ambiguity than capability.优先选择能返回决策所需最小权威对象的 API。一次倾倒大量文本的宽泛端点，往往只会增加歧义。

02 · CONTROL

Execution control执行控制

Authentication, allowlists, scopes, budgets, idempotency, confirmation, and audit logs must live outside the model. Treat generated arguments as untrusted input.认证、白名单、权限范围、预算、幂等、确认和审计日志都应位于模型之外。模型生成的参数必须按不可信输入处理。

03 · EVIDENCE

Evidence quality证据质量

Return source IDs, timestamps, status, and compact fields. The final answer should distinguish provider facts from ChatGPT’s interpretation.返回来源 ID、时间戳、状态与精简字段，让最终答案能够区分服务商事实与 ChatGPT 的解释。

Recommended shortlist推荐清单

Six API families that make ChatGPT workflows useful让 ChatGPT 工作流真正有用的六类 API

This is a use-case shortlist, not a universal ranking. Availability, pricing, quotas, data residency, and terms can change; verify the linked official documentation before production use.这是一份按场景划分的候选清单，而不是放之四海皆准的排名。可用性、价格、配额、数据驻留和条款都可能变化，上线前应检查对应官方文档。

APIAPI	Best ChatGPT job适合的 ChatGPT 任务	Why it fits匹配原因	Main control关键控制
OpenAI web search tool	Current web information with citations带引用的最新网页信息	OpenAI can execute web search inside a Responses API request and return cited sources.OpenAI 可在 Responses API 请求内执行网页搜索并返回带引用的来源。	Citations, source quality, freshness引用、来源质量与时效
GitHub REST API	Issue triage, PR context, checks, release workflowsIssue 分流、PR 上下文、检查与发布流程	Structured repository objects map cleanly to engineering decisions.结构化仓库对象能直接映射到研发决策。	Pin repository and SHA; use fine-grained scopes固定仓库与 SHA；使用细粒度权限
Slack Web API	Channel search, summaries, approval handoffs频道检索、摘要与审批交接	Turns team communication into retrievable events and controlled messages.把团队沟通转化为可检索事件与受控消息。	Channel allowlist; preview before posting频道白名单；发送前预览
Notion API	Knowledge retrieval and structured page updates知识检索与结构化页面更新	Useful when the source of truth is databases and pages rather than chat.适合以数据库和页面而非聊天记录为事实来源的团队。	Limit shared pages and editable properties限制共享页面与可编辑属性
Stripe API	Billing lookup, payment support, approved commerce actions账单查询、支付支持与经批准的交易动作	Strong object model, test environments, request IDs, and idempotency patterns.对象模型清晰，并提供测试环境、请求 ID 与幂等机制。	Never let model text set amount or recipient unchecked金额与收款对象不可直接采用模型文本
Twilio API	SMS, voice, status notifications, support workflows短信、语音、状态通知与客服流程	Makes the final mile of a workflow programmable across channels.让工作流的最后一公里可以跨渠道编程控制。	Consent, recipient allowlist, templates, rate limits同意、收件人白名单、模板与频率限制

API-by-API analysis逐项分析

What each API contributes—and where it should stop每类 API 能解决什么，又该止步于哪里

A useful ChatGPT tool contract is smaller than the provider API. Wrap only the operations the workflow needs, normalize their responses, and keep provider authorization in application code.实用的 ChatGPT 工具契约应小于服务商完整 API。只封装工作流真正需要的操作，统一返回结构，并把服务商授权留在应用代码中。

OpenAI web searchOpenAI 网页搜索

GROUNDING

Use OpenAI web search when an API-built workflow needs current public-web evidence. It can run inside a Responses API request and return cited sources. Preserve citations and timestamps, constrain domains when appropriate, and do not treat a snippet as final evidence.当基于 OpenAI API 构建的工作流需要最新公开网页证据时，可使用 OpenAI 网页搜索工具。它能够在 Responses API 请求内运行并返回带引用的来源。应保留引用与时间戳，必要时限制搜索域名，且不能把摘要片段当成最终证据。

BEST FOR: Research briefs, news monitoring, source-backed answers研究简报、新闻监测、带来源回答
BOUNDARY: Freshness, source quality, allowed domains时效、来源质量、允许域名

GitHub REST API

ENGINEERING

GitHub is a strong first integration for software delivery because issues, commits, pull requests, reviews, and checks are structured objects. Pin every analysis to a repository and SHA. Start with retrieval and triage; generate comments or changes as drafts before submission.GitHub 很适合软件交付场景，因为 Issue、Commit、PR、Review 与 Check 都是结构化对象。每次分析都应固定仓库和 SHA；先从检索与分流开始，评论或变更先生成草稿再提交。

BEST FOR: Issue summaries, release notes, PR evidence, CI diagnosisIssue 摘要、发布说明、PR 证据、CI 诊断
BOUNDARY: Fine-grained scopes, protected branches, human merge细粒度权限、受保护分支、人工合并

Slack Web API

HANDOFF

Slack works best as an event and handoff layer: retrieve a bounded thread, summarize an incident channel, or draft a message carrying evidence from another API. Search and posting need separate tools. Require a visible preview and channel allowlist before sending.Slack 最适合作为事件与交接层：读取限定 Thread、总结事故频道，或起草一条包含其他 API 证据的消息。搜索与发送应拆成不同工具；发送前必须展示预览并检查频道白名单。

BEST FOR: Incident context, approval requests, team notifications事故上下文、审批请求、团队通知
BOUNDARY: Channel scope, retention, preview before post频道范围、保留策略、发送前预览

Notion API

KNOWLEDGE

Notion fits workflows whose source of truth is a curated database or page hierarchy. Preserve page IDs and last-edited times so ChatGPT can flag stale context. For writes, constrain the destination database and editable properties instead of accepting arbitrary page content.当事实来源是整理过的数据库或页面层级时，Notion 很合适。应保留页面 ID 与最后编辑时间，让 ChatGPT 能提示陈旧上下文。写入时要限定目标数据库和可编辑属性。

BEST FOR: Runbooks, product knowledge, decision recordsRunbook、产品知识、决策记录
BOUNDARY: Shared pages, editable properties, stale content共享页面、可编辑属性、内容时效

Stripe API

COMMERCE

Stripe is appropriate for explaining billing state, retrieving payment objects, or preparing a tightly controlled action. Separate lookup from mutation. Resolve customer, currency, amount, and entitlement from trusted application state—not free-form model output.Stripe 适合解释账单状态、查询支付对象或准备受控交易动作。查询与变更必须分离；客户、币种、金额与权益应从可信应用状态解析，不能由模型自由文本决定。

BEST FOR: Invoice support, subscriptions, approved refund preparation发票支持、订阅查询、经批准的退款准备
BOUNDARY: Identity, amount, idempotency, reconciliation身份、金额、幂等、状态核对

Twilio API

MESSAGING

Twilio provides delivery for SMS, voice, and messaging workflows. ChatGPT can select a template and fill bounded variables; the application must resolve the recipient, check consent and quiet hours, enforce rate limits, and record the provider message ID.Twilio 提供短信、语音与消息工作流的交付层。ChatGPT 可选择模板并填写受限变量；应用必须解析收件人、检查同意与免打扰时段、执行限流并记录服务商消息 ID。

BEST FOR: Status alerts, reminders, escalation workflows状态提醒、预约通知、升级处理
BOUNDARY: Consent, recipients, templates, send limits同意、收件人、模板、发送频率

Scope decision: these six families cover current evidence, engineering, team knowledge, transactions, and communications—the dominant same-intent needs behind “best APIs to use with ChatGPT.” Database, CRM, image-generation, and financial-market-data APIs have distinct evaluation criteria and should be separate guides.范围决策：这六类覆盖最新证据、研发、团队知识、交易与消息触达，是“适合 ChatGPT 的最佳 API”背后的主要同意图需求。数据库、CRM、图像生成和金融行情 API 的评估标准差异较大，应分别成篇。

Implementation pattern实施模式

The safe loop: declare, decide, validate, execute, reconcile安全闭环：声明、选择、校验、执行、核对

Declare one narrow function声明一个边界清晰的函数

Name the action precisely, describe when it should and should not be used, keep required parameters minimal, and use enums for bounded choices.精确命名动作，说明适用与禁用场景，减少必填参数，并用枚举限制可选范围。

Let ChatGPT propose the call让 ChatGPT 提议调用

ChatGPT selects the function and emits structured arguments. It has proposed an action; it has not authorized or completed one.ChatGPT 选择函数并生成结构化参数。此时只是提出动作，并不代表动作已获授权或已经完成。

Validate policy in application code在应用代码中执行策略校验

Validate types and business rules, resolve identity server-side, enforce resource and spending limits, and require approval for consequential writes.校验类型和业务规则，在服务端解析身份，限制资源与预算，并要求高影响写操作经过审批。

Execute with a replay strategy带着重放策略执行

Attach request IDs and idempotency keys where supported. Timeouts do not prove failure: inspect remote state before retrying.在服务商支持时附加请求 ID 与幂等键。超时并不能证明失败，重试前必须核对远端状态。

Return compact evidence返回精简证据

Send ChatGPT status, stable IDs, timestamps, source URLs, and only the fields needed to explain the result. Store the full audit event outside the prompt.向 ChatGPT 返回状态、稳定 ID、时间戳、来源链接和解释结果所需字段；完整审计事件保存在 Prompt 之外。

# Illustrative application-side control flow call = chatgpt.propose(tools=[lookup_issue, draft_message]) args = schema.validate(call.arguments) policy.authorize(user, call.name, args) if call.name == "draft_message": approval.require(preview(args)) result = provider.execute(args, request_id=new_id()) return evidence(result.id, result.status, result.updated_at)# 示例：应用侧控制流程 call = chatgpt.propose(tools=[lookup_issue, draft_message]) args = schema.validate(call.arguments) policy.authorize(user, call.name, args) if call.name == "draft_message": approval.require(preview(args)) result = provider.execute(args, request_id=new_id()) return evidence(result.id, result.status, result.updated_at)

Worked patterns实战模式

Three ChatGPT API workflows worth piloting三个值得试点的 ChatGPT API 工作流

The following are implementation patterns, not measured customer outcomes. Each starts with a bounded read, preserves provider evidence, and places consequential writes behind a separate control.以下是实施模式，不是实测客户成果。每个示例都从限定范围的读取开始，保留服务商证据，并把高影响写操作置于单独控制之后。

GITHUB → CHATGPT → SLACK

Release-risk briefing发布风险简报

Fetch the target PR, changed files, reviews, and check runs at a pinned SHA.按固定 SHA 获取目标 PR、变更文件、Review 与 Check Run。
ChatGPT separates observed failures from inferred risk and missing evidence.ChatGPT 区分已观察失败、推断风险与缺失证据。
Draft a Slack handoff with repository links; a reviewer approves posting.起草带仓库链接的 Slack 交接消息，由审核人批准发送。

Success evidence:成功证据： all claims resolve to a PR, check, review, or commit URL.每项结论都能追溯到 PR、检查、Review 或 Commit 链接。

SEARCH → NOTION → CHATGPT

Grounded market brief有依据的市场简报

Use Search grounding for current external facts and retain citations.使用 Search Grounding 获取外部最新事实并保留引用。
Retrieve the relevant Notion decision record and its edit time.检索相关 Notion 决策记录与编辑时间。
ChatGPT highlights agreement, conflict, and stale internal assumptions.由 ChatGPT 标出一致点、冲突点和陈旧内部假设。

Success evidence:成功证据： external statements cite sources; internal claims cite page IDs.外部陈述附来源，内部结论附页面 ID。

STRIPE → CHATGPT → TWILIO

Billing support handoff账单支持交接

Retrieve a customer and invoice from a server-resolved identity.根据服务端解析的身份查询客户和发票。
ChatGPT explains status and drafts the approved response template.ChatGPT 解释状态并起草经批准的回复模板。
The application checks consent, recipient, and send policy before Twilio.应用检查同意、收件人和发送策略后才调用 Twilio。

Success evidence:成功证据： Stripe object and request IDs plus Twilio message SID.保留 Stripe 对象与请求 ID，以及 Twilio 消息 SID。

Failure modes失败模式

What breaks after the demoDemo 之后最容易坏在哪里

Too many similar tools工具数量过多且描述相似

ChatGPT chooses the right provider but the wrong operation. Split reads from writes, use intent-specific names, remove unused parameters, and test deliberately ambiguous requests.ChatGPT 选对服务商却选错操作。应拆分读写工具、使用意图明确的名称、删除无用参数，并用刻意模糊的请求测试。

Provider responses flood context服务商响应淹没上下文

Do not return entire channels, repositories, or page trees. Filter server-side, paginate intentionally, cap text fields, and expose a stable ID for follow-up retrieval.不要返回完整频道、仓库或页面树。应在服务端过滤、主动分页、限制文本字段，并提供稳定 ID 供后续按需读取。

Timeout becomes a duplicate action超时演变成重复动作

A timeout is an unknown state, not proof of failure. Query by request or idempotency key, reconcile remote state, and retry only when the operation is absent or safely repeatable.超时代表状态未知，并不等于失败。应按请求或幂等键查询、核对远端状态，只在动作不存在或可安全重复时重试。

External text changes model behavior外部文本改变模型行为

Issue bodies, web pages, and messages can contain prompt injection. Label retrieved content as data, strip active markup, keep policy in a separate trusted layer, and block tool-scope escalation.Issue 正文、网页和消息都可能包含 Prompt Injection。应把检索内容标记为数据、移除活动标记、把策略置于独立可信层，并阻止工具权限升级。

Validation playbook验证计划

A 14-day pilot before production access接入生产权限前的 14 天试点

Documentation proves an API can perform an operation. A fixed evaluation set proves whether the ChatGPT workflow selects it correctly, remains inside policy, and recovers from realistic failures.文档只能证明 API 可以执行某项操作；固定评测集才能证明 ChatGPT 工作流会正确选用它、始终留在策略范围内，并能从真实故障中恢复。

DAYS 1–3

Baseline the task建立任务基线

Record the manual steps, trusted sources, required evidence, permissions, latency, and final human decision.记录人工步骤、可信来源、必要证据、权限、延迟与最终人工决策。

DAYS 4–7

Test read-only cases测试只读案例

Run normal, missing, stale, paginated, unauthorized, rate-limited, and malformed responses.运行正常、缺失、陈旧、分页、未授权、限流与异常响应案例。

DAYS 8–11

Attack boundaries攻击系统边界

Inject hostile text, force a timeout, rotate credentials, and request forbidden resources. Verify safe stops and clear logs.注入恶意文本、制造超时、轮换凭据并请求禁用资源，确认系统安全停止且日志清楚。

DAYS 12–14

Add one reversible write加入一项可逆写操作

Require preview, approval, idempotency, and reconciliation. Expand only when failure cases are understood.要求预览、审批、幂等与状态核对；只有理解失败案例后才扩大范围。

Go/no-go evidence: tool-selection accuracy on the fixed set, unsupported-claim count, authorization failures, calls per task, latency, cost, recovery quality, and reviewer corrections. Do not invent a universal pass percentage; set thresholds from the risk of the chosen workflow.上线证据：固定评测集上的工具选择准确性、无依据结论数量、授权失败、单任务调用数、延迟、成本、恢复质量与审核修正量。不要虚构通用通过率，应根据所选工作流的风险设定阈值。

Decision framework决策框架

ChatGPT App, GPT Action, direct API tool, MCP, or QVeris?ChatGPT App、GPT Action、API 工具、MCP 还是 QVeris？

ChatGPT App or GPT ActionChatGPT App 或 GPT Action

Use a ChatGPT App for approved connected services, or a GPT Action when a custom GPT must call an API described by OpenAPI. Apps and Actions are separate paths, and workspace controls may limit availability.获准的连接服务优先使用 ChatGPT App；自定义 GPT 需要调用由 OpenAPI 描述的外部 API 时使用 GPT Action。Apps 与 Actions 是两条独立路径，且可能受工作区策略限制。

Direct REST or SDKREST 或 SDK 直连

Best for a stable, application-owned provider with strict performance, schema, or compliance requirements. Your team owns authentication, retries, normalization, and monitoring.适合稳定、由应用长期维护且对性能、Schema 或合规要求严格的服务商。认证、重试、标准化与监控均由团队负责。

MCP

Best when the same model-facing tools should be reusable across compatible clients. MCP standardizes discovery and invocation, but it does not replace provider authorization or business policy.适合同一组模型工具需要跨兼容客户端复用的场景。MCP 可统一发现与调用方式，但不能取代服务商授权和业务策略。

QVeris

Best when the workflow starts from a required capability and may span changing providers. Use the QVeris tool directory to inspect available capabilities, then test non-sensitive inputs in the Playground before wiring production credentials.当工作流从“需要什么能力”出发，并可能跨越不同服务商时更合适。可先在 QVeris 工具目录检查能力，再用 Playground 的非敏感数据验证参数，最后接入生产凭据。

Production controls生产控制

What to test before ChatGPT can take action允许 ChatGPT 执行动作前要验证什么

Security and privacy安全与隐私

Keep keys in a secret store, never in prompts or tool results.密钥保存在密钥系统中，不进入 Prompt 或工具结果。
Separate read and write functions, credentials, and audit policies.分离读写函数、凭据与审计策略。
Treat API content as untrusted; it may contain prompt injection.把 API 内容视为不可信输入，其中可能包含 Prompt Injection。
Minimize personal data sent to the model and log redacted payloads.减少发送给模型的个人数据，并对日志 Payload 脱敏。

Reliability and cost可靠性与成本

Test 401, 403, 404, 409, 429, 5xx, malformed data, and timeouts.测试 401、403、404、409、429、5xx、异常数据与超时。
Cap calls per turn, records per call, payload size, and spend.限制每轮调用数、单次记录数、Payload 大小与费用。
Cache stable reads and parallelize only independent operations.缓存稳定读请求，只并行执行互不依赖的操作。
Measure task completion and reviewer corrections, not demo fluency.衡量任务完成率与审核修正量，而不是 Demo 是否流畅。

FAQ

Questions about APIs and ChatGPT关于 API 与 ChatGPT 的常见问题

Can ChatGPT call external APIs directly?ChatGPT 能直接调用外部 API 吗？

ChatGPT can select a declared function and produce its arguments, but your application is responsible for executing custom functions and returning results. OpenAI-managed tools such as web search are different: OpenAI executes those tools within the API request.ChatGPT 可以选择已声明函数并生成参数，但自定义函数仍由应用负责执行并返回结果。OpenAI 托管工具（例如网页搜索）有所不同：这类工具由 OpenAI 在 API 请求内执行。

What is the best first API for a ChatGPT workflow?ChatGPT 工作流最适合先接入哪个 API？

Choose the API that supports your highest-value, low-risk read task. Search grounding, issue lookup, or internal knowledge retrieval are usually safer pilots than payments, messaging, deletion, or account changes.优先选择能支持高价值、低风险只读任务的 API。搜索 Grounding、Issue 查询或内部知识检索，通常比支付、发消息、删除或账户变更更适合作为首个试点。

Should ChatGPT receive every endpoint from an API?是否应该把一个 API 的所有端点都交给 ChatGPT？

No. Expose a small task-specific tool set. Broad catalogs make tool selection harder and expand the attack surface. Add capabilities only after evaluation shows a real need.不应该。应只暴露少量、针对具体任务的工具。过大的工具目录会增加选择难度和攻击面，只有评估证明有实际需求时才扩展能力。

How do I prevent duplicate actions after a timeout?如何避免超时后重复执行动作？

Use provider-supported idempotency keys or stable request IDs, then query remote state before retrying. Stripe, for example, documents idempotent requests for safe retries. If the provider cannot reconcile state safely, require manual resolution.使用服务商支持的幂等键或稳定请求 ID，并在重试前查询远端状态。例如 Stripe 明确提供幂等请求机制以支持安全重试。若服务商无法安全核对状态，则应转为人工处理。

Does MCP make a ChatGPT API workflow secure?使用 MCP 就能保证 ChatGPT API 工作流安全吗？

No. MCP standardizes how model-facing tools are described and invoked. You still need provider authorization, input validation, least privilege, approval, rate limits, logging, and incident controls.不能。MCP 统一的是模型工具的描述与调用方式；服务商授权、输入校验、最小权限、审批、限流、日志与事件响应仍需单独设计。

Pilot one controlled ChatGPT workflow从一个受控的 ChatGPT 工作流开始

Describe the capability, inspect matching tools and parameters, then test with non-sensitive data. Keep production credentials and consequential writes outside the pilot until the failure cases are understood.先描述所需能力，检查匹配工具和参数，再用非敏感数据测试。只有理解失败场景后，才把生产凭据与高影响写操作纳入试点。

Test a ChatGPT workflow in QVeris在 QVeris 测试 ChatGPT 工作流 Read the QVeris MCP guide阅读 QVeris MCP 指南