Server data from the Official MCP Registry
Run AI interviews, manage candidates and read hiring analytics on JobMojito.
About
Run AI interviews, manage candidates and read hiring analytics on JobMojito.
Remote endpoints: streamable-http: https://mcp.jobmojito.com/mcp
Security Report
This is a well-architected MCP server with proper OAuth authentication, careful permission scoping, and comprehensive security testing. The codebase demonstrates strong security practices including token handling, lazy auth for discovery, session verification with fallback-open semantics, and extensive error-handling guards. Minor code quality observations around exception handling and logging scope do not materially impact the security posture. Supply chain analysis found 1 known vulnerability in dependencies.
4 files analyzed · 7 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
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How to Install & Connect
Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
Documentation
View on GitHubFrom the project's GitHub README.
JobMojito MCP Server
Welcome
JobMojito is an AI interview platform for hiring teams: let AI interview every candidate — you make the call. Lifelike avatar and voice agents run structured, multilingual interviews at any scale, score them in real time, and hand recruiters the transcripts, summaries and reports they need to make the actual decision. Everything the platform produces is decision support for a qualified human reviewer — never the hiring decision itself.
What the platform offers:
- AI avatar & voice interviews — real-time conversational interviews with configurable avatars, generated from a job description or built from your own question set, with a fully branded candidate experience.
- Scoring, transcripts & reports — consistent structured assessment with real-time scoring, plus shareable interview reports for the hiring team.
- Candidate management & invitations — register candidates in bulk, send each one a personal interview link, grant extra attempts, track results.
- Role-play & coaching personas — avatars that play a defined role, for screening scenarios or candidate practice on the coaching portal.
- Knowledge base — upload company documents so interviews and evaluations reflect your organisation's context.
- Workspaces & analytics — merchants and sub-merchants, credit usage, and hiring analytics across positions.
Around the product: the admin console at app.jobmojito.com,
developer/API docs at developer.jobmojito.com,
the help center at help.jobmojito.com, and the
hosted MCP endpoint this repo powers at https://mcp.jobmojito.com/mcp.
This repository is the MCP server that puts all of that into AI assistants like Claude and ChatGPT.
An MCP server for the JobMojito API, built
with FastMCP and designed to deploy on
Prefect Horizon (the MCP platform from the FastMCP
team — app.prefect.cloud → Horizon).
It exposes:
- 25 API tools auto-generated from JobMojito's live OpenAPI spec (interviews
and role-play personas, the coaching catalogue, candidates and results,
knowledge base, merchant lists/analytics). All endpoints — including the
GETlists — are surfaced as tools with clean, curated names, each with a title and read-only/destructive annotations. - 2 documentation tools (
search_documentation,get_documentation) that read the developer docs and help center live — docs stay single-source on their existing platforms; nothing is copied into this repo. - Supabase OAuth so end users can log in directly from Claude, ChatGPT, etc. The signed-in user's Supabase JWT is forwarded to the JobMojito API on every call.
How it fits together
MCP client (Claude / ChatGPT)
│ OAuth login (Supabase OAuth Server, DCR)
▼
JobMojito MCP server (this repo, on Horizon)
│ forwards the user's Supabase JWT
▼
JobMojito API (https://cool.jobmojito.com/functions/v1)
| Concern | Approach |
|---|---|
| API → tools | FastMCP.from_openapi(...), all routes mapped to Tools, curated names via injected operationIds |
| Spec freshness | Fetched live at startup; a runtime cache + committed snapshot are fallbacks |
| Auth | SupabaseProvider (Remote OAuth); per-request JWT forwarding to the upstream API |
| Docs | Built-in tools reading developer.jobmojito.com/llms.txt + .md and the help.jobmojito.com (Featurebase) help center |
Files
| File | Purpose |
|---|---|
server.py | Entry point — builds and exposes mcp (point Horizon at server.py:mcp) |
config.py | Environment-driven settings |
openapi_loader.py | Live fetch + cache/snapshot fallback + operationId injection |
naming.py | Curated tool names, titles, hints and annotations per endpoint |
upstream.py | httpx client that forwards the user's Supabase JWT to the API |
middleware.py | Call logging, upstream-error rewriting, result-size guard, annotation backfill |
merchants.py | Merchant picker (MCP App UI) + list_my_merchants text fallback |
docs_tools.py | search_documentation / get_documentation |
featurebase.py | Featurebase REST client (help-center articles) |
mintlify.py | Mintlify developer-docs MCP proxy + client-credentials auth |
tests/ | test_smoke.py (inventory, schema relaxation, docs) + test_listing_readiness.py (directory contract) |
docs/ | Developer docs: architecture, development, deployment |
scripts/update_snapshot.py | Refresh the committed fallback spec |
scripts/try_docs.py | Local smoke test for the documentation tools |
data/openapi.snapshot.json | Offline fallback spec (regenerate from your machine) |
lazy_auth.py | Unauthenticated capability discovery + scope= on the 401 challenge |
wellknown.py | /healthz, OpenAI domain challenge, Smithery server card |
server.json | Official MCP Registry entry |
.github/workflows/publish-registry.yml | Publishes server.json to the MCP Registry when a push to main changes server.py:SERVER_VERSION (or via manual dispatch) |
Local development & testing (macOS)
# 1. Set up a virtualenv and install deps
python3 -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt
# 2. Configure secrets in .env (auto-loaded; gitignored)
cp .env.example .env # then fill in your keys/credentials
# 3. Static check — see exactly what Horizon will deploy
fastmcp inspect server.py:mcp
# 4. Run the unit tests (offline; uses the snapshot fallback)
ENABLE_AUTH=false pytest -q --asyncio-mode=auto
# 5. Smoke-test the docs tools live (Featurebase + Mintlify federation)
ENABLE_AUTH=false python scripts/try_docs.py "how do I create an interview"
# 6. Run the server and connect a client
ENABLE_AUTH=false python server.py # → http://localhost:8000/mcp
# then, in another terminal, open the MCP Inspector:
npx @modelcontextprotocol/inspector
# transport: "Streamable HTTP", URL: http://localhost:8000/mcp
Testing notes:
- Docs tools (
search_documentation, and the mounted Mintlifysearch_*_developer_*/query_docs_filesystem_*) work withENABLE_AUTH=false— no Supabase login needed.scripts/try_docs.pyis the fastest check. - API tools (
create_interview,list_candidates, …) call the real JobMojito API and need a Supabase user token. For local testing, setJOBMOJITO_DEV_BEARER_TOKENin.envto a valid Supabase access token; it's forwarded whenENABLE_AUTH=false. (Never set this in production — there the token comes from the user's OAuth session.) - Full OAuth locally is rarely needed; if you want it, run with
ENABLE_AUTH=true, setBASE_URL=http://localhost:8000, and connect a client that supports OAuth (it will bounce you through Supabase).
Refresh the fallback snapshot from a network that can reach the API:
python scripts/update_snapshot.py(the committed snapshot in this repo is a thin structural fallback; this replaces it with the full live spec).
Supabase OAuth setup
This server uses Supabase's OAuth Server feature (which supports Dynamic Client Registration, so MCP clients self-register). The MCP server is the OAuth resource server — it validates tokens; Supabase issues them.
Project: https://momsbvnltsydezmoesqt.supabase.co
SupabaseProvider derives every endpoint from this project URL:
| Endpoint | URL |
|---|---|
| Authorize | …/auth/v1/oauth/authorize |
| Token | …/auth/v1/oauth/token |
| JWKS | …/auth/v1/.well-known/jwks.json |
| OIDC discovery | …/auth/v1/.well-known/openid-configuration |
Steps:
- Supabase Dashboard → Authentication → OAuth Server
- Enable the OAuth Server and Allow Dynamic OAuth Apps
- Site URL:
https://app.jobmojito.com - Authorization Path:
/oauth/consent
- Env:
SUPABASE_PROJECT_URL=https://momsbvnltsydezmoesqt.supabase.co,BASE_URL=https://mcp.jobmojito.com(public base, no/mcp),SUPABASE_JWT_ALGORITHM=ES256(switch toRS256if your JWKS shows RSA keys). - If the JobMojito Edge Functions require an
apikeyheader, setSUPABASE_ANON_KEY.
Consent is handled by Supabase / your app, not this server. Because the Site
URL is app.jobmojito.com, Supabase serves the approve/deny screen at
https://app.jobmojito.com/oauth/consent, where the user already has a Supabase
session. This MCP server is only the OAuth resource server — it does not serve a
consent page. SITE_URL and OAUTH_CONSENT_PATH are informational and should
match your Supabase OAuth Server settings.
Token note:
SupabaseProvidercannot validate token audience (Supabase Auth doesn't implement RFC 8707 resource indicators yet). This is expected and logged at startup.
Authentication model
Every tool call requires the user to be signed in via Supabase OAuth —
including search_documentation and get_documentation. Keep ENABLE_AUTH=true;
the signed-in user's token is forwarded to the JobMojito API so calls respect that
user's permissions.
The one deliberate exception is capability discovery: with ENABLE_LAZY_AUTH
(default true), initialize, ping and the */list methods answer without a
token so directory crawlers can render the tool list. No data is reachable that
way — every tools/call, resource read and prompt still needs a verified JWT.
Deploy to Prefect Horizon
- Push this repo to GitHub.
- At horizon.prefect.io, sign in with GitHub and select this repo.
- Configure:
- Entrypoint:
server.py:mcp - Dependencies: auto-detected from
requirements.txt - Horizon Authentication: off — this server provides its own Supabase OAuth, so let it be the auth layer.
- Entrypoint:
- Set environment variables / secrets:
ENABLE_AUTH=trueBASE_URL=https://mcp.jobmojito.com— critical. This must be the server's public base URL, with no/mcpand no trailing slash. It's whatSupabaseProvideradvertises as the OAuth resource; if it's left at thehttp://localhost:8000default, clients get401 invalid_token. The startup log printsbase_url=…and warns if it's localhost.SUPABASE_PROJECT_URL=https://momsbvnltsydezmoesqt.supabase.coSUPABASE_ANON_KEYif the Edge Functions need theapikeyheader.FEATUREBASE_API_KEYfor help-center docs.
- Deploy. Your MCP endpoint is
https://mcp.jobmojito.com/mcp. Horizon redeploys on every push tomain.
Testing the login
A 401 on initialize is the normal first step of MCP OAuth — the client is
meant to read the discovery metadata and run the Supabase login. Horizon's
Inspector / ChatMCP do not perform that login, so they'll show a bare 401.
Test by adding https://mcp.jobmojito.com/mcp as a custom connector in
Claude.ai, which runs the full OAuth flow and prompts the Supabase login.
Make sure the Supabase side is configured (or the flow 401s regardless): OAuth
Server enabled + Dynamic Client Registration on; Site URL https://app.jobmojito.com
- Authorization Path
/oauth/consent; and that consent page hosted on the app.
Because the OpenAPI spec is fetched live at startup, each redeploy picks up the latest JobMojito API automatically.
Keeping documentation single-source
Docs are not duplicated here. search_documentation builds a live index and
get_documentation fetches a page on demand, both reading the source platforms
directly. Edit docs there and the MCP reflects changes within the cache TTL
(DOCS_CACHE_TTL_MINUTES, default 60).
| Source | How it's read | Credentials |
|---|---|---|
developer.jobmojito.com (Mintlify) | Mintlify MCP mounted into this server (semantic search + query_docs_filesystem, incl. the imported OpenAPI) when client credentials are set; else public llms.txt/.md via the built-in tools | MCP client id/secret (to federate) |
help.jobmojito.com (Featurebase) | REST API if FEATUREBASE_API_KEY is set (structured articles incl. body), else public-HTML scraping | API key (optional) |
Why this server and Mintlify
Mintlify imports the OpenAPI, but its MCP is read-only documentation — it lets an agent search and read the API reference. It cannot call the API. This server turns the same OpenAPI into authenticated, callable tools (acting as the signed-in Supabase user). So: Mintlify answers "how does it work?"; this server "does the thing." The federation mounts Mintlify's doc-search tools alongside the action tools so end users get both from one connector.
Developer docs: Mintlify federation
developer.jobmojito.com is a Mintlify site whose MCP exposes search +
query_docs_filesystem tools (including the imported OpenAPI). This server mounts
it as a proxy. When federated, the built-in developer-llms.txt source is
disabled to avoid duplication.
Public by default (no credentials). Mintlify serves a public MCP at /mcp.
Because the developer docs are public, DEVELOPER_DOCS_MCP_URL defaults to
https://developer.jobmojito.com/mcp and is mounted with no auth — it works out
of the box.
Authenticated endpoint (optional). Mintlify also offers an /authed/mcp
endpoint with OAuth client-credentials, for group-restricted content. It is
not enabled by default — the site's /.well-known/mcp only advertises a
public server until you enable it. To use it:
- Mintlify dashboard → MCP server page → Enable MCP Server (otherwise
/authed/mcp/oauth/tokenreturns 404). - Create a client credential there (MCP client credentials, not Mintlify
API keys) → set
DEVELOPER_DOCS_MCP_CLIENT_ID/_CLIENT_SECRET. - Set
DEVELOPER_DOCS_MCP_URL=https://developer.jobmojito.com/authed/mcp.
Auth is attached only when the URL contains /authed and both credentials
are set; the server then exchanges them at {url}/oauth/token and
caches/refreshes the token.
Featurebase: which credential is which
Featurebase exposes docs three ways — the credential shape tells you which:
- REST API → a single API key (sent as
Authorization: Bearer <key>andX-API-Key), basehttps://do.featurebase.app. Create it in the Featurebase dashboard: log in via auth.featurebase.app/choose-org → Settings → Advanced → API → copy the key. (The direct/settings/apiURL 404s — you must enter through your org first.) This is what this server uses for the help center (setFEATUREBASE_API_KEY). - Hosted MCP (
mcp-read.featurebase.app, the Reader connector) → interactive OAuth (authorization code + PKCE, no client secret). Designed for a human to click "Connect" in Claude/ChatGPT. Best added directly as a connector in your AI client, not proxied from this server (there's no machine token / client-credentials grant). - Public web →
llms.txt/.md(developer docs), no auth.
A Client ID + Client secret pair is not a Featurebase docs credential — neither the REST API (API key) nor the MCP (PKCE, no secret) uses that shape. If you have one, it's likely a Featurebase SSO/identity OAuth app or from a different system. For docs, use the REST API key above.
Featurebase Reader MCP (not federated)
Unlike Mintlify, Featurebase's Reader MCP (mcp-read.featurebase.app) only
supports interactive OAuth (no client-credentials), so it isn't mounted here. If
you want its native search, add it directly as a connector in your AI client.
HELP_DOCS_MCP_URL is kept in config for reference only.
Directory listings & discoverability
The server is built to satisfy the Anthropic connector directory, the OpenAI plugin directory (ChatGPT + Codex) and the official MCP Registry without further code changes. What that means in practice:
| Requirement | Where it lives |
|---|---|
Every tool has a title + readOnlyHint/destructiveHint, with a written justification | naming.py::TOOL_META, applied by server.py::_customize_component, backfilled by middleware.ToolMetadataBackfillMiddleware |
| Read and write are separate tools (no catch-all) | naming.py — asserted in tests/test_listing_readiness.py |
tools/list works without credentials, so crawlers can show the tool list | lazy_auth.py |
scopes_supported in the protected-resource metadata, scope= on the 401 | server.py::_build_auth + lazy_auth.WWWAuthenticateScopeMiddleware |
| Actionable errors instead of bare 4xx/5xx | middleware.UpstreamErrorMiddleware |
| Results stay under the client's size ceiling | middleware.ResultSizeGuardMiddleware |
| Health probe for uptime monitoring | GET /healthz |
| OpenAI domain verification | GET /.well-known/openai-apps-challenge (set OPENAI_APPS_CHALLENGE_TOKEN) |
| MCP Registry entry | server.json + the publish workflow |
Generate the annotation justifications OpenAI asks for at submission:
python -c "import naming,json;print(json.dumps(naming.annotation_justifications(),indent=2))"
Verify the public identity after any deploy or hostname change — this is the single most common way an otherwise-healthy server 401s every client:
curl -s https://mcp.jobmojito.com/.well-known/oauth-protected-resource/mcp
# "resource" MUST equal "https://mcp.jobmojito.com/mcp"
curl -s https://mcp.jobmojito.com/healthz
Still to do outside this repo
The code is ready; these are not code problems:
- A Claude Team or Enterprise plan. The Anthropic submission portal lives
under
claude.ai/admin-settings/and is unavailable on individual plans. - A public "Connect JobMojito to Claude & ChatGPT" docs page — required by Anthropic (documentation URL) and OpenAI (support URL).
- A populated reviewer test account with no MFA and no email confirmation step; OpenAI rejects submissions whose test account requires either.
- DNS TXT record on
jobmojito.comfor thecom.jobmojito/*registry namespace, and theMCP_REGISTRY_PRIVATE_KEYrepo secret — see the header comment in.github/workflows/publish-registry.yml. - Allowlist Anthropic's egress range
160.79.104.0/21on the MCP host and anything in front of Supabase. A blocking WAF is Anthropic's most common documented failure mode.
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