agent4.io

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

• 连接方式: 在云端运行
• 传输方式: Streamable HTTP
• 分类: 搜索与 AI 记忆
• 你需要填写：X-API-Key

安装

选择你使用的 AI 应用，然后复制设置。

通过 2/3 项检查 · 你的提问会经过开发者的服务器（api.agent4.io）

claude mcp add --transport http agent4-tenant https://api.agent4.io/v1/mcp --header 'X-API-Key: your-value'

{
  "mcpServers": {
    "agent4-tenant": {
      "url": "https://api.agent4.io/v1/mcp",
      "headers": {
        "X-API-Key": "your-value"
      }
    }
  }
}

{
  "servers": {
    "agent4-tenant": {
      "type": "http",
      "url": "https://api.agent4.io/v1/mcp",
      "headers": {
        "X-API-Key": "your-value"
      }
    }
  }
}

哪些应用可以使用它

依据这个服务器的连接方式和各应用自己的文档，检查于 2026年11月10日。

通过互联网连接，适用于

ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast

全部应用及其优缺点 →

它能做什么

工具名称和描述与服务器在 2026年11月10日 报告的完全一致。这些内容由作者撰写，不是我们写的；我们以纯文本形式显示。

• list_agents

  List all agents in this tenant (name + published state).

• get_agent

  Get one agent's full configuration (soul/task/tools/skills/knowledge_bases/model/params).

• create_agent

  Create an agent. `name` is lower-cased on save — it is a key, not a display name. soul = persona/identity; task = duties and boundaries; tools = tool-name whitelist (check list_tools first; the system tools time/geo/weather **and `compute_chart`** are **auto-enabled by default**,

• update_agent

  Update **part** of an agent — fields you don't pass stay as they are. ⚠️ List-field semantics, don't mix them up: `tools=[...]` / `skills=[...]` / `knowledge_bases=[...]` are **full-list replacement** — items you didn't read first get pushed out. To "add one / remove one", use `a

• list_tools

  List tool names assignable to agents, with their descriptions (incl. the tenant's connected MCP tools).

• list_mcp_servers

  List the MCP servers connected in this tenant's tool library (read-only; secret fields omitted).

• create_share

  Create a **share / integration entry point** for an agent — this is how end users actually reach it. **`published=True` only means "visible", not "reachable"**: for end users to talk to the agent you must create a share. The response carries a directly openable chat link (`{publi

• list_shares

  List an agent's shares (token / label / disabled / chat link / embed URL / appearance config). When the top-level `pretty_url` is non-empty it is the preferred link to give humans (see create_share).

• configure_share

  Configure this share — its name and its **appearance** — fields you don't pass stay as they are (server-side partial merge). - `label`: the name at the top of the chat page, and the browser tab's title. **Renaming a share is this call**; you never need to create a replacement and

• set_pwa_branding

  Configure a specific **agent's** PWA branding and install experience (applies to that agent's `/s/` standalone chat pages — what gets installed to the home screen is one agent's entry page, so each agent is its own app). - `agent`: the agent name whose install branding to configu

• set_custom_domain

  Bind the client's own domain to this tenant's chat pages: `https://chat.client.com/` serves the tenant's branded page (or a specific agent's chat), the address bar keeps the client's domain, and the TLS certificate is issued automatically. **Have the client configure DNS first**:

• list_skills

  List this tenant's skills.

• get_skill

  Get one skill's full content (including the complete instructions text).

• create_skill

  Create a skill. description = "when to use" (goes into the system prompt, keep it short); instructions = the detailed guide (fetched on demand via load_skill). The paradigm (important): instructions are visible only AFTER the model calls load_skill — if calling some tool is **man

• update_skill

  Update part of a skill — fields you don't pass stay as they are (server-side PATCH merge, no GET+PUT round-trip). ⚠️ `tools=[...]` is **full-list replacement**; to add/remove one use `add_tools`/`remove_tools` (incremental, idempotent). Tools bound to a skill take effect automati

• test_skill_trigger

  Reality-check whether your prompts actually trigger tool calls (dry-run) — run this after writing/changing a skill instead of counting corpses in production. Replays your messages N times against the **production** system-prompt assembly, tool schemas and this tenant's actual mod

• list_knowledge_bases

  List this tenant's knowledge bases (with doc/chunk counts and relevance cutoff).

• get_knowledge_base

  Get one knowledge base's configuration (including the full instructions text shown to the model).

• create_knowledge_base

  Create a knowledge base. **Write `description` — it is what routes questions to this base.** Before each answer the platform reads every attached base's `description` and decides which ones this question needs; a base whose description is vague or blank gets searched when it shou

• update_knowledge_base

  Update part of a knowledge base — fields you don't pass stay as they are (server-side PATCH merge).

• add_knowledge_text

  Add a **text** document to a knowledge base (chunking + embedding happen synchronously; returns the real chunk count). For **local files** (pdf/docx…) see `add_knowledge_file`.

• add_knowledge_file

  Add a local file's content to a knowledge base (txt/md/html/pdf/docx). **This MCP runs on the platform server and cannot read paths on YOUR machine.** For text files, read the content yourself and call `add_knowledge_text`; for binaries (pdf/docx), upload via the console, or curl

• search_knowledge_base

  Search this knowledge base; returns matching chunks with distances. Uses **exactly the same retrieval path as real conversations** — use it to validate the cutoff and chunking: an empty result means this question will be judged "not covered" and the agent will answer "not in the

• build_knowledge_index

  Build (or rebuild) the structured index for a knowledge base — the second leg beside vector search. Vector search answers "what does this passage say". It **cannot count, filter numerically or aggregate**, so "how many documents", "which ones are between 1000 and 2000 words", "ho

• get_knowledge_index

  Show the structured index profile: per column coverage, type, numeric range, top values, warnings. **The warnings are the point.** On a real 4,500-document catalogue this surfaced three data problems nobody knew about: 1,058 documents with `page_count` 0, 505 with `reading_level`

• patch_knowledge_index

  Change the structured index schema from one sentence of plain language. Example requests: "also track the author so users can find other books by them", "I want to filter by illustrator", "drop the cover link". The model may only emit add/modify/remove/refused — it cannot rewrite

• improve_prompt

  Rewrite a field's text to work better as an AI system prompt; returns the improved text. field ∈ persona | task | greeting | storyline_task | storyline_opening | storyline_ai_trigger | storyline_ai_criteria | skill_description | skill_instructions | kb_description | kb_instructio

• diagnose_prompt

  Read a field and return a list of **specific** improvement suggestions (string array). field: same values as improve_prompt. current = the text to diagnose (required — an empty text has nothing to diagnose). Typical flow: diagnose_prompt first, pick the suggestions you want, then

• test_planner_trigger

  Dry-run the Dynamic Planner's escalation judge: would these messages be offered a step-by-step plan? Use it after editing the agent's `task`, since the task text is the **business-domain gate** — a vague task lets out-of-domain requests through, a narrow one turns real customers

• preview_plan

  Generate a plan for a goal and return it for review **without persisting anything** — no temporary storyline, no enrollment, no user affected. Use it to inspect plan quality before trusting the feature in production, or to see how the agent's `task` constrains the steps. Returns

• usage_stats

  Usage statistics. group ∈ total | agent | user | space | day | model. Metadata only — token counts and event counts, never any conversation content. Use group="user" to see who uses the most, group="agent" for the busiest agent.

• tenant_info

  This tenant's basic info and quota (plus custom-domain binding status, if any).

• search_agent4_docs

  Search agent4.io's own product docs — concepts (what a thing *is*) and cookbook recipes (which tool to *call*). Use when you're unsure how an agent4.io feature works, what a term means, or how to build something on the platform. Returns top passages with title, layer ("concept"|"

• list_end_users

  List this tenant's **end users** (the people chatting with your agents) — roster only, never any conversation content. Each user carries: display name, login method (email / oauth:* / proxy), email (if any), space/session/document counts, last-24h token usage, and a `console_url`

• get_end_user

  Get one end user's detail: basic profile (name, contact email/phone, city, timezone) + their spaces. Never any conversation content. Carries a `console_url` to the user's detail page.

• list_user_sessions

  List one end user's **sessions** — metadata only: agent, title (AI summary), message count, tokens, timestamps. **Message bodies are not returned.** Transcripts are rendered in the console: each session carries a `console_url` that **deep-links straight to that conversation, auto

• list_page_contexts

  List all page playbooks of this tenant (with match rules, greeting mode, position).

• upsert_page_context

  Create or fully replace a page playbook. `context` is the page background the **server** injects for the agent — write "who lands on this page, what they are deciding, what they usually worry about"; do NOT write facts like prices or quotas (those belong in a knowledge base, whic

• resolve_page_context

  Given a URL (or key), show which playbook it resolves to — always verify after writing a match rule. Globs make it easy to write rules that "look right but never match" (one `*` short, one path level too many) — and in production the only symptom is visitors silently getting the

• page_context_stats

  Open counts and suggested-question click counts per playbook — find copy nobody clicks.

• list_storylines

  List this tenant's storylines (optionally filtered by agent). Includes state, version, default flag.

• get_storyline

  Get one storyline's full definition (whole graph + profile_schema + top-level fields).

• create_storyline

  Create a storyline draft. After creating, self-check with validate_storyline, then publish_storyline. user_visibility — what the end user sees of their own run: "invisible" (default, no UI), "named" (a banner with the storyline name only), "trail" (banner + read-only view where u

• update_storyline

  Update **part** of a storyline draft — fields you don't pass stay as they are (GET-then-merge on top of a full PUT underneath). concurrency: "user" = progress belongs to the person (shared across sessions); "session" = progress belongs to the case (one run per session). Changes a

• validate_storyline

  Validate the storyline graph (entry / dead ends / unreachable / dangling / cross-line targets / rule dimensions). Returns {ok, errors}. Must pass before publishing.

• publish_storyline

  Publish a storyline: validates first (blocking errors → 422), then freezes an immutable version and marks it published.

• unpublish_storyline

  Unpublish (archive): no more auto-enrolment; in-flight users silently degrade to the plain agent on their next turn (progress kept — re-publishing resumes it).

• clone_storyline

  Clone a storyline into a new draft (new key, unpublished, doesn't claim default, no chain pointer) for tweaking.

• export_storyline

  Export a portable storyline JSON (schema_version + definition; no tenant/version/id) for backup, migration or re-import.

• import_storyline

  Import an exported storyline JSON as a draft. **Artifacts like "generate a storyline from a novel / source material" land here.** payload = the structure returned by export_storyline (schema_version + graph + profile_schema + top-level fields). Version-aware: payloads newer than

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月11日

• ! 注意

  作者与仓库一致

  注册中心没有列出源代码仓库，因此无法将发布者（agent4.io）与代码对应起来

• … 尚未检查

  仍在维护

  我们还没有从 GitHub 读取这个仓库

• … 尚未检查

  有许可证

  我们还没有从 GitHub 读取这个仓库

• ✓ 通过

  端点有响应

  在 327 毫秒内响应（HTTP 200）

• – 不适用

  使用 OAuth 登录

  无需登录

• ✓ 通过

  工具描述中没有隐藏指令

  已读取 50 个工具描述，未发现针对 AI 的隐藏指令

用户评价

还没有评价

用 Google 登录后写评价

与“搜索与 AI 记忆”中的其他服务器比较i

• 星标数多于此分类中其他 5911 个服务器的 0%
• 发布到注册中心的时间比此分类中其他 5911 个服务器的 26% 更新
• 基础检查结果等于或优于此分类中其他 5911 个服务器的 45%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

替代选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：↓ 每周下载量i★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Ruflo

Agent teams, swarms, memory and hooks for Claude Code and Codex, served over MCP.

作者：ruvnet·广泛使用·↓ 7.4万/周·★ 8.1万·昨天更新

在你的电脑上运行

安装

Context7

Up-to-date docs for AI agents

作者：upstash·广泛使用·↓ 125万/周·★ 6.5万·前天更新

电脑或云端

安装

Metabase

Lets AI clients search, explore, query, and visualize data in a Metabase instance.

作者：metabase·广泛使用·★ 5万·6个月前更新

在云端运行

安装

作者的 README

仓库中没有找到 README