Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Knuckles-Team/jellyfin-mcp --skill jellyfin-mcp-developmentgit clone --depth 1 https://github.com/Knuckles-Team/jellyfin-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/knuckles-team/jellyfin-mcp/jellyfin-mcp-development)<a href="https://agentmods.dev/skills/knuckles-team/jellyfin-mcp/jellyfin-mcp-development"><img src="https://agentmods.dev/badge/skills/knuckles-team/jellyfin-mcp/jellyfin-mcp-development/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/knuckles-team/jellyfin-mcp/jellyfin-mcp-development"><img src="https://agentmods.dev/badge/skills/knuckles-team/jellyfin-mcp/jellyfin-mcp-development.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00061 | $0.01154 |
| Opus 5.5 | $0.00024 | $0.00462 |
| Sonnet 5.5 | $0.00012 | $0.00231 |
| Haiku 4.5 | $0.00006 | $0.00115 |
Grade A, and why
jellyfin-mcp-development scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Jellyfin MCP Development
This package is the Jellyfin connector for the agent-connector-sdk. Keep changes
bound to the existing connector surface and verify the packaged assets together with
the runtime code.
Source map
pyproject.tomldeclares thejellyfin-mcpconsole script atagent_connector_sdk.cli:serveand theagent_connector_sdk.connectorentry pointjellyfin_mcp:connector.jellyfin_mcp/mcp_server.py(import pathjellyfin_mcp.mcp_server) registers the MCP server and action-routed tools.jellyfin_mcp/api/api_client_base.pyand theapi_client_{library,media,system,user}.pymodules own the Jellyfin REST calls;jellyfin_mcp/auth.pyowns credential and delegated-auth setup.jellyfin_mcp/connector_sources.pydeclares live source metadata. Keep it aligned withjellyfin_mcp/ontology/media.ttl,ontology/mappings/source.yaml,ontology/fixtures/records.json, andontology/migrations/manifest.json.- Packaged
skills/**,ontology/**,mcp_config.json, and related assets are included by the[tool.setuptools.package-data]declaration inpyproject.toml.
Configuration and safety
Use environment or secret injection for JELLYFIN_URL, JELLYFIN_API_KEY,
JELLYFIN_USERNAME, JELLYFIN_PASSWORD, and the inherited auth/delegation values
(AUTH_TYPE, ENABLE_DELEGATION, DELEGATED_SCOPES, JELLYFIN_AUDIENCE, and the
OIDC_* settings). MCP_TOOL_MODE and the CONDENSED_JELLYFINTOOL toggle select
the served tool surface. OIDC delegation uses the configured token exchange and
TLS profile. Do not commit credentials, live endpoints, or captured personal media
data. Preserve TLS verification and the connector SDK's auth and policy boundaries
when changing clients or tool registration.
Focused checks
Run the smallest relevant tests before the repository gates. The existing focused
coverage is in tests/test_env_declarations.py, tests/test_auth_header.py,
tests/test_action_discovery.py, tests/test_init_dynamics.py, and the KG tests
under tests/test_kg_*.py. Use a task-local environment and run:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today First seen · 96 lines · 61 tokens per session scan A bf11aed7026c
jellyfin-mcp-development is a skill published in the GitHub repository Knuckles-Team/jellyfin-mcp (3 stars, last pushed yesterday), licensed MIT. It adds 61 tokens to every session and 1,154 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-28.
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