DongneSOS MCP
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@DongneSOS MCPclassify a broken streetlight in Gangnam"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
DongneSOS MCP
동네SOS / 이거 어디에 말해? PlayMCP candidate implementation.
This server helps a user prepare a civic inconvenience report without doing the reporting for them. It classifies a Korean neighborhood issue, explains what evidence to prepare, and drafts a neutral copy/paste report. It never submits a report, logs in, reads KakaoTalk, collects precise location, uploads photos, or calls external government APIs.
MCP Tools
classify_civic_issue: classifies the issue into the fixed 28-item taxonomy, routes it to a channel family, and returns the canonical Pro Chat output fields:result_type,priority,routing,draft_policy, anderrors.draft_civic_report: creates a neutral report preparation draft for non-emergency cases only.
The server intentionally exposes exactly those two tools. Both tools declare
MCP inputSchema and outputSchema; the HTTP smoke verifies those schemas are
visible in tools/list.
Related MCP server: Korean Land MCP
Safety Boundaries
Emergency or immediate-danger inputs return
emergency_redirectorblocked_emergency; draft generation is blocked.PII-like text is masked before draft output.
Defamation, punishment demands, and legal certainty phrases are neutralized.
Channel routing is advisory. Users must verify the real local government channel before submitting.
presentation_mockis a lightweight ChatGPT card shape, not a dependency on Kakao Widget APIs.
Local Run
npm install
npm run check
npm run smoke:http
npm run smoke:dist
npm run dev -- --host 127.0.0.1 --port 3000After npm run build, production start uses:
npm startContainer build:
docker build -t dongnesos-mcp .
docker run --rm -p 3000:3000 dongnesos-mcpPlayMCP in KC image builds require linux/amd64, including on Apple Silicon:
npm run image:build:amd64
npm run image:push:playmcpnpm run image:push:playmcp is a dry-run by default. It only pushes after
external image publication is approved and the command is run with
DRY_RUN=0 CONFIRM_EXTERNAL_IMAGE_PUSH=1.
Container release smoke:
npm run smoke:docker
npm run preflight:release
npm run package:deploy
npm run verify:bundle
npm run evidence:submissionEndpoints:
GET /healthzPOST /mcp
Verification
npm run validate:data
npm run scan:policy
npm test
npm run build
npm run smoke:http
npm run smoke:dist
npm run smoke:docker
npm run preflight:release
npm run package:deploy
npm run verify:bundle
npm run evidence:submissionAfter deployment, verify the public endpoint and write review evidence:
MCP_URL=https://<kakao-cloud-endpoint>/mcp \
EVIDENCE_OUT=deploy/playmcp/evidence/remote-smoke.json \
npm run smoke:endpointThe current acceptance target is at least 48 passing tests plus the HTTP MCP
smoke covering tools/list schemas, classify_civic_issue, and
draft_civic_report.
For the review narrative and sample cases, see DEMO_SCRIPT.md.
For owner approval and external deployment stop rules, see
deploy/playmcp/owner-approval-packet.md.
For the contest path, deploy through PlayMCP in KC first, copy its Endpoint
URL, then temporarily register that endpoint in the PlayMCP developer console.
See deploy/playmcp/playmcp-in-kc-registration.md for the exact field mapping.
For a clean source bundle that excludes node_modules, dist, and local
evidence files, run npm run package:deploy and use the tarball under
deploy/playmcp/package/.
To prove the latest tarball works from a clean extraction, run
npm run verify:bundle.
After local or remote smoke runs, npm run evidence:submission writes a
review-ready evidence draft to
deploy/playmcp/evidence/submission-evidence.generated.md.
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