Planning Center MCP

Live

OAUTH 2.1

SERVICE SCHEDULING

Project Management

Planning Center MCP gives agents authenticated access to service scheduling: search teams, songs, and plans, and pull who's scheduled to serve.

  • Per-user credentials: each call uses the actual user's token, never a shared bot.
  • Encrypted per-tenant vault: AES-256, resolved at request time, never in LLM context.
  • Scoped before every call: pre-call scope check, 90-day SIEM-exportable audit chain.
Planning Center MCP
agent · Acme Q3
Run
Who's on the Worship team for Sunday, and what songs are in the set list?
S
planningcentermcp_services_plans
112ms
Planning Center agent
Sunday 9am plan: 4 songs including 'Great Are You Lord'. Worship team: 6 people scheduled, 1 unconfirmed.
Sources: 1 plan, 1 team
planningcentermcp
1 plan
18:29
Message Claude...

Tools your ops agent reaches for on Planning Center, scoped per user.

CALL ANY TOOL
Search service schedules end to end: teams, songs, plans, and who's serving, scoped to each user's own Planning Center access.
planningcentermcp_services_service_types
Search service types
Search for service types, the containers for plans, teams, schedules, and song lists for a recurring worship event.
Parameters
Name
Type
Required
Description
name
string
Optional
Filter service types by name, partial match.
ids
array
Optional
Filter to only return service types with these IDs.
planningcentermcp_services_plans
Search plans
planningcentermcp_services_teams
Search teams
planningcentermcp_services_team_positions
Search team positions
planningcentermcp_services_songs
Search songs
planningcentermcp_services_schedules
Get schedules
Build your Agent
Same auth pattern across LangChain, OpenAI, Anthropic, and Google ADK.
Python · LlamaIndex
import { ScalekitClient } from "@scalekit-sdk/node";
import { createReactAgent } from "@langchain/langgraph/prebuilt";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);

// Planning Center tools scoped to this user
const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["planningcentermcp"], toolNames: [
    "planningcentermcp_services_service_types",
    "planningcentermcp_services_plans",
    "planningcentermcp_services_teams"] },
  pageSize: 100,
});

const agent = createReactAgent({ llm, tools });
await agent.invoke({ messages: [{ role: "user", content: "Who's on the Worship team for Sunday, and what's the set list?" }] });
import OpenAI from "openai";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);
const openai = new OpenAI();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["planningcentermcp"] }, pageSize: 100,
});

const res = await openai.chat.completions.create({
  model: "gpt-5",
  messages: [{ role: "user", content: "Who's on the Worship team for Sunday, and what's the set list?" }],
  tools,
});

// Execute the tool call with the user's vaulted planningcentermcp credential
await sk.tools.executeTool(res.choices[0].message.tool_calls[0], "user_123");
import Anthropic from "@anthropic-ai/sdk";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);
const anthropic = new Anthropic();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["planningcentermcp"] }, pageSize: 100,
});

const msg = await anthropic.messages.create({
  model: "claude-sonnet-5",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Who's on the Worship team for Sunday, and what's the set list?" }],
  tools,
});

// Tool call runs with the user's vaulted planningcentermcp credential
await sk.tools.executeTool(msg.content, "user_123");
import { Agent } from "@google/adk/agents";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["planningcentermcp"] }, pageSize: 100,
});

const agent = new Agent({
  name: "planningcentermcp_agent",
  model: "gemini-2.5-pro",
  instruction: "Planning Center tools scoped to this user",
  tools,
});

await agent.run("Who's on the Worship team for Sunday, and what's the set list?");
Try these prompts
Copy any prompt into your agent. Each maps directly to a Planning Center MCP tool. Click to copy, paste into your agent, done.
Sunday planning
Copy the prompt
Copied
Who's on the Worship team for Sunday's plan?
Copy the prompt
Copied
What songs are in this week's set list?
Copy the prompt
Copied
Search plans for the Sunday 9am service type from the last month.
Teams and songs
Copy the prompt
Copied
Search teams named 'Production'.
Copy the prompt
Copied
Find songs by author 'Chris Tomlin'.
Copy the prompt
Copied
List team positions for the Vocals team.
My schedule
Copy the prompt
Copied
What am I scheduled to serve in this month?
Copy the prompt
Copied
Get the schedule for person 88231.
Copy the prompt
Copied
Search service types across the organization.
SEE HOW AUTH WORKS
Your users connect once. Their Planning Center MCP credentials stay vaulted, every call is checked, and every action is logged.
1
Authorize
Your user connects
Planning Center MCP
once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access
Who:
user ‘A’
when:
Once per user
access:
Limited to user
2
Store
Their
Planning Center MCP
token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection
vault:
encrypted
scope:
per-user
tokens:
auto-refreshed
3
Resolve
When your agent calls a
Planning Center MCP
tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs
speed:
~40ms
check:
before every call
seen by:
nobody
4
Audit
Every
Planning Center MCP
tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it
history:
90 days
export:
SIEM-ready
logged:
every call
Test other agents
See the same per-user auth pattern across other project-management and scheduling connectors.
ENGINEERING
Engineering standup agent
Aggregate GitHub and GitLab activity, link to Jira, and post a daily standup digest to Slack. No async updates.
ENGINEERING
Auto-release notes agent
Group merged GitHub PRs by feature, fix, or chore and publish release notes per tag. No manual changelog grooming.
Why Scalekit
Secure your agent's access. Connectors ship in minutes
Other connector libraries treat auth as a demo afterthought. Scalekit starts with identity, scope enforcement, and audit. Connectors follow.
01.
Shared tokens break per-user analytics
A shared Planning Center MCP token looks fine in a demo. In production every schedule lookup looks like one service account, and you cannot tell which user triggered it. Scalekit resolves the credential of the actual user who triggered the agent, never a shared bot.
// shared token
audit → bot_service_account

// scalekit
audit → user_abc ✓
02.
Authentication is not authorization
03.
Multi-tenancy is architectural
04.
Planning Center MCP today. Ten connectors tomorrow.
“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”
Venu Madhav Kattagoni
Head of Engineering / Von
FAQs
Frequently Asked Questions
Does the agent access Planning Center MCP as the user or through a shared key?
As the user. Scalekit resolves the credential of the person who triggered the agent at request time, so every Planning Center MCP action in your audit trail is attributed to a real user, not a shared service account.
Where is the Planning Center MCP token stored?
In an AES-256 encrypted vault with per-tenant namespacing. Tokens are resolved at request time, never enter LLM context, refresh automatically, and can be revoked from one dashboard.
Can I limit what the agent does in Planning Center MCP?
Yes. Filter by tool name in listScopedTools to expose only what you want. Scalekit also enforces scope checks before every API call.
What happens when a user revokes access?
The credential is invalidated at the next tool call. The call fails closed, other users' connections are unaffected, and the revocation is logged in the audit chain.
Can the agent see people's personal contact information through Planning Center People?
Only the fields your scoped tool set exposes. Keep the agent to the services_* tools for schedule and song-library read access without touching the people_* tools that carry household and contact data.
Start in your coding agent
Up and running in one command
Install the Scalekit skill in your editor of choice. Connector, auth, tools, prompt, all wired up
Claude Code REPL
/plugin marketplace add scalekit-inc/claude-code-authstack
/plugin install agentkit@scalekit-auth-stack
Cursor Code REPL
# ~/.cursor/mcp.json
{
""mcpServers"": {
""planningcentermcp"": {
""url"": ""https://mcp.scalekit.com/planningcentermcp"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Codex Code REPL
# ~/.codex/config.toml
[mcp_servers.planningcentermcp]
url = ""https://mcp.scalekit.com/planningcentermcp""
auth_env = ""SCALEKIT_TOKEN""
Copilot Code REPL
# .vscode/mcp.json
{
""servers"": {
""planningcentermcp"": {
""url"": ""https://mcp.scalekit.com/planningcentermcp"",
""type"": ""http""
}
}
}