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MCP server for interacting with Overseerr media request management system
Overseerr MCP has 3 clearly defined tools with partial implementation quality. All tools have names starting with action verbs (get_*), and all have descriptions and input schemas visible in the source code. However, there are significant gaps: (1) tool names are inconsistent ('overseerr_status' vs 'overseerr_get_status' in descriptions vs code), (2) parameter descriptions exist but lack context about valid ranges and practical constraints, (3) output schemas are completely undocumented, callers cannot know what fields to expect from the JSON responses, (4) error handling guidance is absent, no recovery hints or categorization, and (5) parameters lack proper documentation about dependencies and filtering behavior. The implementation uses fastmcp/HTTP (good transport), validates inputs locally (status enum check), but does not expose this validation to the schema or describe error recovery paths. Parameter naming is acceptable but could be more explicit about date format expectations.
Get a list of movie requests from Overseerr. Can be filtered by status (e.g., 'approved', 'pending') and start date.
Get the current status and version of the Overseerr server.
Get a list of TV show requests from Overseerr. Can be filtered by status (e.g., 'approved', 'pending') and start date.
Output schemas completely undocumented. Tools return JSON via TextContent with no declared structure. LLMs cannot plan downstream extraction or know what fields exist.
Error handling completely absent. No error recovery guidance, no categorization (retryable vs user-fixable vs fatal), no suggestions when filters reject all items or API fails. Code does not validate or surface errors to LLM.
Parameter descriptions lack critical constraints. 'start_date' shows format hint in description but no min/max, no semantics of filtering (is it >=, <=, ==?), and no guidance on what happens if date is invalid. 'status' enum is declared but no description of what each status means operationally.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | F | 49 | <=2025-11-25 | v2 |
| 2026-03-09 | D | 54 | - | v1 |
No pagination metadata in output. Tools fetch all pages internally (skip/take loop) but return flat list with no total count, no next_cursor, no page info. If result set is large, LLM has no way to limit memory or iterate efficiently.
Tool names inconsistent between code constant names and descriptions. Code uses 'overseerr_status' but README/docs reference 'overseerr_get_status'. This mismatch will confuse LLMs and users about the correct invocation name.
No sensible result limits enforced. Movie/TV request tools fetch and return all matching records via pagination loop. If an Overseerr instance has thousands of requests, response token count could explode and exhaust context window. No cap documented.
Response field naming unclear. Tools return formatted results with fields like 'title', 'media_availability', 'request_date' but there is no schema definition. Downstream tools or agents will not know if field names use snake_case, camelCase, or vary per API response. Breaks tool chaining.