智能体
dev.to ·
@Datawright Labs
用 Apify MCP 服务器为 AI 智能体接入网页数据工具（Python，无 SDK）
教程介绍 Apify 在 mcp.apify.com 托管的 MCP 服务器，可通过 URL 的 tools 参数把 Store 中的 Actor（SSL 检查、DNS 审计、死链爬取等）暴露为智能体可调用的工具，使用 Apify API token 鉴权并按结果计费，并给出约 50 行仅用标准库的 Python 客户端示例。
AI推荐理由 给出 Apify 托管 MCP 服务器通过 ?tools= 参数暴露 Store Actor 为工具、以 Bearer token 鉴权、按结果计费的具体用法，并附约 50 行纯标准库 Python 客户端，对 Agent 工具接入有实操参考；但属第三方教程，未提供效果评测，且带有推广自家 Actor 的倾向。
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正文
Most AI agents can now talk to remote MCP servers. Apify runs one at https://mcp.apify.com, and any public Actor in Apify Store can be exposed through it as a tool your agent can call: SSL checks, DNS audits, broken-link crawls, screenshots, keyword research and thousands more.
This post shows what actually happens on the wire, with a ~50-line stdlib Python client, so you can see exactly what your agent sees and pays for.
1. Pick the tools with the URL
?tools= takes a comma-separated list of Actors:
https://mcp.apify.com?tools=datawright-labs/ssl-certificate-checker,datawright-labs/email-domain-dns-checker
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Auth is your Apify API token as Authorization: Bearer (free account; Actors bill per result on your own account).
2. The client
"""Call Apify Store Actors as MCP tools from plain Python (stdlib only).
Usage: APIFY_TOKEN=... python3 mcp_agent_tools.py
"""
import json, os, urllib.request
TOOLS = "datawright-labs/ssl-certificate-checker,datawright-labs/email-domain-dns-checker"
URL = f"https://mcp.apify.com?tools={TOOLS}"
HEADERS = {
"Authorization": "Bearer " + os.environ["APIFY_TOKEN"],
"Content-Type": "application/json",
"Accept": "application/json, text/event-stream",
}
def rpc(body, session=None):
h = dict(HEADERS)
if session:
h["mcp-session-id"] = session
req = urllib.request.Request(URL, data=json.dumps(body).encode(), headers=h)
with urllib.request.urlopen(req, timeout=180) as r:
text = r.read().decode()
sid = r.headers.get("mcp-session-id") or session
# Streamable HTTP may answer as SSE ("data: {...}") or plain JSON
msgs = [json.loads(l[5:]) for l in text.splitlines() if l.startswith("data:")]
return (msgs[-1] if msgs else (json.loads(text) if text.strip() else None)), sid
# 1. Handshake
_, sid = rpc({"jsonrpc": "2.0", "id": 1, "method": "initialize",
"params": {"protocolVersion": "2025-03-26", "capabilities": {},
"clientInfo": {"name": "tutorial", "version": "1"}}})
rpc({"jsonrpc": "2.0", "method": "notifications/initialized"}, sid)
# 2. What tools does the agent see?
tools, _ = rpc({"jsonrpc": "2.0", "id": 2, "method": "tools/list"}, sid)
for t in tools["result"]["tools"]:
print(f"- {t['name']}: {t.get('description', '')[:90]}")
# 3. Call one, exactly like an agent would
name = next(t["name"] for t in tools["result"]["tools"] if "ssl-certificate-checker" in t["name"])
res, _ = rpc({"jsonrpc": "2.0", "id": 3, "method": "tools/call",
"params": {"name": name, "arguments": {"domains": ["example.com", "github.com", "expired.badssl.com"]}}}, sid)
for c in res["result"]["content"]:
print(c.get("text", "")[:1500])
# 4. The call returns a run summary; the rows come from get-dataset-items (the agent's next step)
run = json.loads(res["result"]["content"][0]["text"])
ds = run["storages"]["datasets"]["default"]["id"]
items, _ = rpc({"jsonrpc": "2.0", "id": 4, "method": "tools/call",
"params": {"name": "get-dataset-items",
"arguments": {"datasetId": ds, "limit": 20,
"fields": "host,status,daysUntilExpiry,issuerOrganization,problems"}}}, sid)
for c in items["result"]["content"]:
print(c.get("text", "")[:2000])
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3. What the agent sees
tools/list returns one tool per Actor (datawright-labs--ssl-certificate-checker, datawright-labs--email-domain-dns-checker) plus four helpers: get-actor-run, get-dataset-items, get-key-value-store-record, abort-actor-run.
4. The two-step call (the part most guides skip)
Calling the Actor tool runs it and returns a run summary, not the rows: status, run time, item count, the field list and a nextStep hint telling the agent to call get-dataset-items. Good agents follow that hint; if yours stops at "SUCCEEDED", tell it to fetch the dataset items. Passing fields= keeps the tokens down:
{"host":"example.com","status":"ok","daysUntilExpiry":63,"problems":[]}
{"host":"github.com","status":"ok","daysUntilExpiry":37,"problems":[]}
{"host":"expired.badssl.com","status":"expired","daysUntilExpiry":-4212,"problems":["Certificate expired","Not trusted: CERT_HAS_EXPIRED"]}
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That whole round trip took about 9 seconds and cost $0.003 (3 hosts at $1 per 1,000).
5. Plug the same URL into your agent
Any client that supports remote Streamable HTTP MCP servers with a header takes the same two values (URL + Bearer header). Two configs we tested end to end for connection and tool discovery:
Hermes (pip install "hermes-agent[mcp]"), ~/.hermes/config.yaml: mcp_servers: { datawright: { url: "...", headers: { Authorization: "Bearer ${APIFY_TOKEN}" } } }, then hermes mcp test datawright.
OpenClaw: openclaw mcp add datawright --no-probe --url "..." --transport streamable-http --header 'Authorization=Bearer ${APIFY_TOKEN}', then openclaw mcp probe datawright (the pre-save probe doesn't expand ${APIFY_TOKEN}, hence --no-probe).
6. Gotchas
Agents only see the top 10 results of Apify's search-actors, so pin the Actors you want with ?tools= instead of letting the agent search.
/sse is gone; use the Streamable HTTP endpoint above.
Keep the token in an env var or your client's secret store, never in a prompt.
Disclosure: the two example Actors are ours (Datawright Labs). Any Store Actor works the same way.