Testing Mcp Tools Locally

作者 PostHog469d1773e9cb无许可证收录于 2026年10月8日更新于 2026年10月8日

Set up the local dev environment, seed data, and API keys to test the staff-only managed migrations MCP tools (managed-migrations-support-list, managed-migrations-support-get) end to end. Use when testing batch import support tooling, debugging MCP tool responses or discovery (tools not appearing), or verifying the support API before deploying. Covers the discovery gate: hidden scope, is_staff, user:read, and why wildcard keys and OAuth never work.

AI 生成的概览

搭建本地开发环境、种子数据和 API 密钥,端到端测试仅限员工使用的托管迁移 MCP 工具。

功能
说明如何启动本地开发环境、运行 Postgres 迁移、验证数据库连通性,并创建处于不同状态的 BatchImport 记录。介绍如何将用户设为员工并签发带有所需权限范围的个人 API 密钥,然后用 curl 调用支持 API,并通过 Hono 服务器和 MCP Inspector 调用 MCP 工具。还说明了工具发现门槛以及常见故障的排查清单。
适用场景
适用于在本地测试批量导入支持工具、排查 MCP 工具响应或工具未出现等发现问题,或在部署前验证支持 API。
运行要求
需要运行中的本地开发环境及 Docker 服务、已应用的 Postgres 迁移、hogli 命令行工具、services/mcp 中基于 pnpm 的 Hono MCP 服务器,以及用于 MCP Inspector 的 npx。还需要员工用户和带有 batch_import_support:read 与 user:read 权限范围的个人 API 密钥。仅为说明文档,不包含脚本。

Testing managed migrations MCP tools locally

Prerequisites

The dev environment must be running with Docker services healthy. The batch import support API and MCP tools require:

  • A staff user (is_staff = True)
  • A Personal API Key carrying both batch_import_support:read and user:read, explicitly
  • Postgres migrations applied (ClickHouse not required)

Why both scopes: the backend accepts batch_import_support:read alone, but MCP tool discovery verifies staffness via /api/users/@me/ and hides the tools (fail-closed) when the key cannot make that call. A * wildcard does not substitute for either — the discovery gate requires the hidden scope explicitly, and the backend's INTERNAL scope handling rejects wildcard keys outright. For the production setup flow, see docs/support-mcp-tools.md.

1. Start the dev environment

bash
hogli start -dhogli wait

If hogli wait fails on migrate-persons-db or migrate-behavioral-cohorts, those are optional separate databases — ignore them. If it fails on migrate-postgres, check Docker port forwarding (see troubleshooting below).

2. Run Postgres migrations

bash
hogli migrations:run

ClickHouse migration failures are fine — batch imports only need Postgres.

3. Verify DB connectivity from the Django shell

bash
hogli dev:shell-plus -y -- -c "from posthog.models import Team, Userprint(Team.objects.first(), User.objects.first())"

If this fails with connection refused on port 5432, see troubleshooting below.

4. Seed batch import test data

Use hogli dev:shell-plus to create BatchImport records in various states. The secrets field is an EncryptedJSONStringField — empty {} serializes to null and violates the NOT NULL constraint; always pass a non-empty dict.

python
from products.managed_migrations.backend.models.batch_imports import BatchImport
BatchImport.objects.create(    team=team,    created_by_id=user.id,    status=BatchImport.Status.PAUSED,    import_config={        'source': {'type': 's3', 'bucket': 'test', 'region': 'us-east-1', 'prefix': 'data/'},        'data_format': {'type': 'json_lines', 'skip_blanks': True, 'content': {'type': 'mixpanel'}},        'sink': {'type': 'capture'},    },    secrets={'access_key': 'test', 'secret_key': 'test'},    state={'parts': [        {'key': 'part-1', 'current_offset': 50000, 'total_size': 50000},        {'key': 'part-2', 'current_offset': 10000, 'total_size': 50000},        {'key': 'part-3'},    ]},)

See references/seed-data.md for a full seeding script covering all statuses.

Important: the local batch-import-worker process will pick up RUNNING records and may modify their status (e.g. pausing them due to config validation errors). To keep records stable for testing, either stop the worker or use COMPLETED/FAILED/PAUSED statuses.

5. Make your user staff and mint test keys

Mint fresh keys rather than editing scopes on an existing one — the MCP server caches a key's scopes per token, so edited scopes can serve stale results.

python
from posthog.models import Userfrom posthog.models.personal_api_key import PersonalAPIKeyfrom posthog.models.utils import generate_random_token_personal, hash_key_value
me = User.objects.first()me.is_staff = True; me.save()
def mint(user, scopes):    token = generate_random_token_personal()    PersonalAPIKey.objects.create(user=user, label=str(scopes)[:40], secure_value=hash_key_value(token), scopes=scopes)    return token
print(mint(me, ["batch_import_support:read", "user:read"]))

To test the negative cases of the discovery gate, also mint: a ["*"] key (tools must NOT appear), a ["batch_import_support:read"] key without user:read (tools must NOT appear — staff lookup fails closed), and the full pair on a non-staff user (tools must NOT appear).

6. Test the API directly

bash
# List all batch importscurl -H "Authorization: Bearer <token>" \     http://localhost:8010/api/managed_migrations_support/ | jq
# Get detail for a specific importcurl -H "Authorization: Bearer <token>" \     http://localhost:8010/api/managed_migrations_support/<uuid>/ | jq

7. Test via MCP

Run the Hono server, not pnpm run dev. The wrangler worker (pnpm run dev, port 8787) proxies /mcp to production mcp.us.posthog.com unless MCP_HONO_URL is set, so local keys get 401 Invalid API key. The Hono server serves MCP directly against the local API:

bash
cd services/mcpcp .dev.vars.example .dev.vars   # POSTHOG_API_BASE_URL=http://localhost:8010pnpm run dev:hono                # serves http://localhost:3001/mcp

Authenticate with the PAT as a Bearer header, never the OAuth flow. The hidden scope is structurally absent from OAuth — signing in through the inspector's OAuth login can never surface these tools.

The Hono server runs exec mode: tools/list returns a single exec tool, and real tools are discovered and invoked through it. Test with the MCP Inspector CLI:

bash
# Discovery — should list both support tools for the staff key, none for the othersnpx @modelcontextprotocol/inspector --cli http://localhost:3001/mcp \  --header "Authorization: Bearer <token>" \  --method tools/call --tool-name exec --tool-arg "command=search managed-migrations-support"
# Invocation — end-to-end through Djangonpx @modelcontextprotocol/inspector --cli http://localhost:3001/mcp \  --header "Authorization: Bearer <token>" \  --method tools/call --tool-name exec --tool-arg "command=call managed-migrations-support-list {}"

Expected discovery matrix:

keytools visible
staff user, batch_import_support:read + user:readboth
staff user, * onlynone
staff user, batch_import_support:read without user:readnone (staff lookup fails closed)
non-staff user, both scopesnone (and direct API calls 403)

The interactive Inspector UI (http://localhost:6274) also works — paste the PAT as the Bearer token in connection settings instead of using its OAuth login.

Troubleshooting

401 "Invalid API key" from localhost:8787

You're talking to the wrangler worker, which proxies /mcp to production — your local key is invalid there. Use the Hono server on port 3001 (see step 7), or set MCP_HONO_URL=http://localhost:3001 in .dev.vars.

Tools don't appear for a key that should see them

Check, in order:

  1. The key carries batch_import_support:read explicitly — * does not match hidden scopes.
  2. The key also carries user:read (or *) — the discovery staff check reads /api/users/@me/ and fails closed.
  3. The key's user has is_staff = True.
  4. The key was minted with those scopes from the start — the MCP server caches scopes per token, so mint a fresh key instead of editing an existing one.

Port 5432 not reachable from host

The posthog-db-1 Docker container may have stale port mappings (container created days ago without the current port binding config). Fix by force-recreating:

bash
docker compose -f docker-compose.dev.yml -f docker-compose.profiles.yml \  up -d --force-recreate db

Verify: nc -z 127.0.0.1 5432 should succeed.

secrets={} causes NOT NULL violation

EncryptedJSONStringField encrypts the value — an empty dict serializes to null. Always pass a non-empty dict: secrets={'placeholder': 'true'}.

Batch import worker modifies seeded records

The local batch-import-worker process automatically claims RUNNING records. If it encounters a config validation error (e.g. missing skip_blanks), it will pause the import with a detailed Rust backtrace in status_message. Stop the worker or seed with non-RUNNING statuses to prevent this.

The gates, end to end

A request passes through two independent layers:

  1. MCP discovery (presentation): a tool requiring an OAuth-hidden scope surfaces only when the key explicitly carries the scope AND /api/users/@me/ confirms is_staff — otherwise it is hidden, fail-closed (services/mcp/src/lib/staff-only-tools.ts).
  2. Django enforcement (the security boundary): IsAuthenticated + IsStaffUser + APIScopePermission with scope_object = "INTERNAL" and batch_import_support:read. Sessions need staffness only; PATs need staffness plus the explicit scope; *-only keys always 403.

来源与署名

来源:PostHog/ai-plugin位于skills/testing-mcp-tools-locally提交469d177

许可证: 无许可证

内容归原作者所有。SourceWeft 从公开仓库中收录这些内容。

举报或申请下架

更多来自 PostHog/ai-plugin 的技能

Writing Simplified Technical English

PostHog

应用 ASD-STE100 简化技术英语规则,让智能体撰写的文字含义明确、便于执行。

Writing & Content2026年10月8日

Working With Task Comments

PostHog

通过 PostHog MCP exec 调度器读取并解读 PostHog 任务、产物和画布上的评论。

Productivity & Workflow2026年10月8日

Working With Skills

PostHog

指导智能体使用 PostHog 的 skill-* MCP 工具来发现、读取、创建、更新和重构技能。

AI & Agents2026年10月8日

Working With Scouts

PostHog

关于如何把监控任务委派给 PostHog Signals 侦察代理、处理其报告并长期调校整个代理集群的操作手册。

AI & Agents2026年10月8日

Validating And Publishing Canvases

PostHog

Validate and publish a canvas source project safely: the source-project shape, declared capabilities, reading the current version pointer, iterating on validation diagnostics, guarded publishing with expected_current_version_id, staging a draft build and promoting it, waiting out the queued build, and recovering from a 409 version_conflict or a 429 capacity limit without overwriting concurrent work. Use whenever a canvas edit is ready to save, a draft build is wanted, a canvas publish or build returns diagnostics or a conflict, or a task needs to understand canvas version history.

待分类2026年10月8日

Understanding Billing Usage

PostHog

Explains PostHog billing usage and spend from the customer's visible Billing MCP tools. Use when the user asks why usage or spend is high, which product or project is driving usage, what a usage type means, how to reduce usage, what changed over time, why they got a usage change alert, or whether a spike/drop alert was real or noisy. Also use before product-specific analytics skills when the user names a billable PostHog product metric such as events, recordings, feature flag requests, exceptions, survey responses, synced rows, logs, AI events, AI credits, or Inbox credits. Starts from Billing usage/spend tools, then routes to customer-visible product MCP surfaces for deeper investigation.

待分类2026年10月8日