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oratilo

oratilo-mcp

by oratilo
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oratilo-mcp

MCP server for oratilo — a shared library of YouTube videos re-edited into concept-structured summaries.

What it's for: before an agent spends work summarizing a video, it can check whether a summary already exists. A cache is only a cache if something reads it.

Install

Node 18+. No dependencies. Plain MCP over stdio, so any MCP client can run it.

Claude Code

claude mcp add --scope user oratilo -- npx -y oratilo-mcp

Codex CLI — codex mcp add, or in ~/.codex/config.toml:

[mcp_servers.oratilo]
command = "npx"
args = ["-y", "oratilo-mcp"]

Kimi CLI — /mcp-config in the TUI, or in ~/.kimi/mcp.json:

{
  "mcpServers": {
    "oratilo": { "command": "npx", "args": ["-y", "oratilo-mcp"] }
  }
}

Anything else — the JSON block above is the common shape (Claude Desktop, Cursor, Windsurf, Cline …); drop it into that client's MCP config file. If you drive GLM / Z.ai or another model through one of these clients, configure the client, not the model provider.

Verify with /mcp in whichever client you used.

Related MCP server: YouTube Tools MCP Server

What you get

Prompt — summarize. One command for people. Give it a YouTube link; it asks which language you want, looks the video up in oratilo, and hands back the existing summary if there is one. If there isn't, it summarizes the video for you normally.

If your client doesn't support MCP prompts, you won't see this command — that's fine. The server sends the same guidance in its instructions at connect time, so just ask in plain language ("summarize this video: ") and the agent will check the library first.

Tool — oratilo_lookup. Exact check for one video. Returns the full summary plus provenance: source, format, updated, and the model recorded when it was generated. Miss means the library doesn't cover that video.

Tool — oratilo_search. Full-text search over the library when you don't have a URL — by topic, phrase, person or company. Returns ranked matches with page links and snippets; follow up with oratilo_lookup for the full text.

Both tools take an optional lang (ko · en · ja · es; default ko).

Verifying a summary

Claims carry footnote markers [n] that map to a timestamp list at the end of each summary. Deep-link source + &t=<seconds>s to check any single claim against the video itself. oratilo stores no transcripts — a summary is an original re-edit, not a transcription.

Scope and limits

  • Read-only. oratilo is a single-author library today; there is no contribution endpoint, so a miss simply means the video isn't covered.

  • The server talks only to oratilo.com public data. It never contacts YouTube.

  • The corpus is small and deliberately curated — expect misses.

  • Summaries can be wrong. Every page has a correction-report link, and updated changes when a page is revised.

ORATILO_BASE may point the server at a localhost origin for development. Any other host is refused and the server falls back to oratilo.com — otherwise a hostile origin could feed an agent invented text as "oratilo's summary". Responses from a development origin carry a warning and drop the citation guidance.

License

MIT.

Status: oratilo is a personal archive — the library is not indexed and is not accepting contributions. This server still works as a read-only lookup against it.

Available Tools

2 tools
oratilo_lookupA

Check whether oratilo (a shared library of concept-structured video summaries) already has a summary for a specific video, BEFORE spending work summarizing it yourself. Returns the full summary plus provenance metadata on a hit. A miss means the video is not covered — summarize it yourself. Accepts YouTube URLs or video ids (arXiv ids reserved for the future).

ParametersJSON Schema
NameRequiredDescriptionDefault
langNoPreferred language (default ko)
sourceYesYouTube URL / 11-char video id / arXiv id

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so the description carries the full burden. It discloses the hit/miss behavior ('Returns the full summary plus provenance metadata on a hit. A miss means the video is not covered'), which is valuable behavioral context beyond what a schema would convey. It lacks some depth (e.g., what provenance metadata entails on a miss) but covers the core behavioral contract well.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three focused sentences, well front-loaded with the decision-critical use case. Each sentence earns its place: purpose, hit/miss outcome, and accepted input formats. Minor redundancy with the schema's source description but overall tight and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-lookup tool with a simple 2-param schema and no output schema, the description is reasonably complete. It explains the decision workflow, hit/miss outcome, and accepted input types. It could benefit from noting what's returned on a miss and clarifying that this isn't a fuzzy search (contrast with sibling), but given the tool's simplicity the coverage is strong.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and both parameters are described adequately in the schema. The description adds value by explaining accepted source formats ('YouTube URLs or video ids') and noting arXiv ids are 'reserved for the future,' which constrains interpretation beyond the raw schema text. Baseline 3 raised for the added source-format context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Check whether') plus resource ('oratilo... has a summary') plus context ('BEFORE spending work summarizing it yourself'). It clearly distinguishes from the sibling tool oratilo_search by indicating this is an exact lookup vs search. The purpose is unambiguous and actionable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit when-to-use guidance: 'Check... BEFORE spending work summarizing it yourself.' It also states what to do on a miss ('summarize it yourself'), providing exclusions. Distinguishes from alternatives by naming when not to rely on it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 2 tool updatesv0.2.0
    • First observedoratilo_lookup
    • First observedoratilo_search
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TDQS

A4.1/5.0
Disambiguation5/5

The two tools have clearly distinct purposes: lookup is for checking a specific video ID/URL for existing coverage, while search is for discovering what content exists by topic when no specific URL is known. The descriptions explicitly clarify when to use each, leaving no ambiguity whatsoever.

Naming Consistency4/5

Both tools follow a consistent oratilo_ prefix with a clear verb (lookup, search). The pattern is consistent and predictable, though with only two tools the naming convention is minimally demonstrated.

Tool Count3/5

At 2 tools, the surface feels thin for a library with search and retrieval capabilities, though it could be argued these two operations are the core of what's needed. The count is borderline but reasonable given the limited scope described.

Completeness3/5

Core read operations (lookup and search) are covered, providing a functional surface. However, there are no write/contribution tools (e.g., adding or updating a summary), so the surface covers only the lookup half of the workflow and leaves the 'summarize it yourself' path entirely to the agent.

Maintenance

ActivityMaintained
ResponsivenessSyncing

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