podcasts
Server Details
An MCP server that provides tools to discover and retrieve podcast episodes transcripts.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.1/5 across 5 of 5 tools scored.
Each tool serves a distinct purpose: fetching latest episodes, retrieving transcripts via GUID, providing feedback, keyword search, and semantic topic search. The descriptions clearly differentiate the two search tools.
All tools follow a consistent verb_noun pattern with underscores: get_latest_episodes, get_transcript, give_feedback, search_episodes, search_episodes_by_topic. The naming is clear and predictable.
Five tools is well-scoped for a podcast transcript server. It covers essential operations without unnecessary bloat, balancing search, retrieval, and feedback.
Core workflows are covered: search (both keyword and semantic), getting latest episodes, and fetching transcripts. However, lacking a direct way to list all shows or episodes by show without searching is a minor gap.
Available Tools
5 toolsget_latest_episodesGet Latest EpisodesARead-onlyIdempotentInspect
Return the most recent transcript-ready episodes across the full podcast catalog.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | Sort order for results. `relevance` ranks full-text searches first and falls back to newest-first when no query is provided. | published_desc |
| limit | No | Maximum number of episodes to return. Must be between 1 and 50. | |
| published_after | No | Inclusive lower publication-date bound. Accepts YYYY-MM-DD or ISO 8601 datetime. | |
| published_before | No | Inclusive upper publication-date bound. Accepts YYYY-MM-DD or ISO 8601 datetime. |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | Number of episodes returned. |
| episodes | Yes | Matching transcript-ready episodes. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, so the bar for transparency is lower. The description adds useful context by specifying 'transcript-ready', indicating episodes have transcripts available. No behavioral contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that conveys the essential purpose with no unnecessary words. Every part earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the rich input schema (100% parameter coverage) and existence of an output schema, the description is sufficiently complete for a simple list tool. It could mention that results are paginated or limited, but the schema covers that via the limit parameter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description does not add additional meaning beyond what the schema provides for each parameter. It could have explained the sort order or date range usage more directly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Return', the resource 'episodes', and the scope 'most recent transcript-ready episodes across the full podcast catalog'. It distinguishes from sibling tools like search_episodes (search) and get_transcript (individual transcript).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives. It implies its use for the latest episodes, but no guidance is given on when to prefer it over search_episodes or search_episodes_by_topic.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_transcriptGet TranscriptARead-onlyIdempotentInspect
Fetch a bounded transcript chunk for a specific episode using its show and episode GUIDs. Use next_cursor to continue reading.
| Name | Required | Description | Default |
|---|---|---|---|
| cursor | No | Zero-based character offset into the transcript. Use the `next_cursor` returned by a prior get_transcript call to fetch the next chunk. | |
| max_chars | No | Target maximum number of transcript characters to return. Chunks prefer natural boundaries and may be slightly shorter. Must be between 100 and 20000. | |
| show_guid | Yes | Podcast show GUID returned by `search_episodes` or `get_latest_episodes`. | |
| episode_guid | Yes | Episode GUID returned by `search_episodes` or `get_latest_episodes`. |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | Transcript chunk text. |
| char_end | Yes | Exclusive zero-based end offset of this chunk in the complete transcript. |
| has_more | Yes | Whether another get_transcript call is needed to continue reading. |
| show_guid | Yes | Podcast show GUID requested by the client. |
| char_start | Yes | Inclusive zero-based start offset of this chunk in the complete transcript. |
| show_title | Yes | Podcast show title. |
| next_cursor | No | Cursor to pass to the next get_transcript call, or null at the end. |
| total_chars | Yes | Total character count of the complete transcript text. |
| episode_guid | Yes | Podcast episode GUID requested by the client. |
| rss_feed_url | Yes | RSS feed URL for the podcast show. |
| episode_title | Yes | Podcast episode title. |
| published_date | Yes | Episode publication timestamp in ISO 8601 format. |
| duration_seconds | No | Episode duration in seconds when available from the source feed. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare safe read-only behavior (readOnlyHint, idempotentHint). Description adds valuable context about chunk boundaries and cursor-based pagination, enhancing transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no redundant words. Front-loaded with key action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given high schema coverage, output schema present, and clear annotations, the description covers all essential behavioral aspects (chunking, cursor usage) for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and each parameter is well-described. Description adds minor detail (zero-based offset, natural boundaries) but mostly repeats what schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb (Fetch), resource (transcript chunk), and scope (specific episode via GUIDs). It distinguishes from sibling tools like search_episodes which search for episodes, not transcripts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to use `next_cursor` for continuation, implying pagination. No explicit when-not-to-use or alternatives, but context makes it clear this tool is for transcript retrieval only.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
give_feedbackGive FeedbackAInspect
Send structured feedback about bugs, missing data, unclear behavior, or feature requests.
| Name | Required | Description | Default |
|---|---|---|---|
| feedback | Yes | Feedback for the server team. Include the problem, missing capability, or suggested improvement without sensitive user data. |
Output Schema
| Name | Required | Description |
|---|---|---|
| status | Yes | Feedback persistence status. |
| message | Yes | Human-readable result summary. |
| feedback_id | Yes | Stable feedback identifier. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations (readOnlyHint=false, destructiveHint=false) are consistent. Description adds behavioral note about avoiding sensitive data. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no fluff, front-loaded with verb and resource. Every word serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given simplicity, description covers purpose and constraint. Output schema exists but not used in description. Could mention result but not necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers the single parameter with description; tool description adds minor context (types of feedback) but doesn't significantly increase understanding beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb 'send' plus resource 'structured feedback' with explicit types: bugs, missing data, unclear behavior, feature requests. Distinguishes from sibling tools about episodes/transcripts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage for reporting issues, but no explicit guidance on when to use vs alternatives, nor when not to use. Lacks exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_episodesSearch EpisodesARead-onlyIdempotentInspect
Search indexed podcast episodes by keyword or show name and return the show/episode GUIDs needed for transcript retrieval.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | Sort order for results. `relevance` ranks full-text searches first and falls back to newest-first when no query is provided. | relevance |
| limit | No | Maximum number of episodes to return. Must be between 1 and 50. | |
| query | No | Optional search keywords matched against indexed episode content. Use people, topics, companies, or phrases. | |
| podcast_name | No | Optional podcast title or internal label to narrow results to a specific show. | |
| published_after | No | Inclusive lower publication-date bound. Accepts YYYY-MM-DD or ISO 8601 datetime. | |
| published_before | No | Inclusive upper publication-date bound. Accepts YYYY-MM-DD or ISO 8601 datetime. | |
| published_within_hours | No | Filter episodes published in the past X hours. Maximum 168 hours (1 week). |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | Number of episodes returned. |
| episodes | Yes | Matching transcript-ready episodes. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds no further behavioral context such as result limits, pagination, authentication requirements, or data freshness. It merely restates the basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence (19 words) that conveys the essential purpose and output. Every word earns its place; no superfluous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the rich parameter descriptions (7 optional params, 100% coverage) and annotations, the description adequately explains the core function. However, it does not mention the output schema or any edge cases (e.g., empty results), leaving it somewhat incomplete for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with each parameter having a detailed description (e.g., sort order, limit bounds, filter semantics). The tool description does not add meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('Search indexed podcast episodes'), specifies the input method ('by keyword or show name'), and explicitly mentions the return value ('show/episode GUIDs needed for transcript retrieval'). This distinguishes it from siblings like get_latest_episodes (no search) and search_episodes_by_topic (topic-based search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing to find episodes by keyword or show name for transcript retrieval, but it does not explicitly state when to use this tool versus alternatives like search_episodes_by_topic or get_latest_episodes. No exclusions or context signals are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_episodes_by_topicSearch Episodes by TopicARead-onlyIdempotentInspect
Semantic topic search across the podcast catalog. Unlike search_episodes (which does lexical/keyword matching), this tool understands meaning: a query for 'AI safety' will match episodes about 'AI alignment', 'AGI risk', or 'frontier model evaluation' even if they don't contain the exact phrase. Returns ranked episodes with the matched topic phrases so you can explain why each result is relevant before fetching the transcript. Best for conceptual or thematic queries — use search_episodes instead when the user is looking for a specific person, product, or verbatim phrase.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of episodes to return. Must be between 1 and 50. | |
| topic | Yes | Semantic topic to find episodes about. Free-form phrasing welcome — the server embeds this string and finds episodes whose extracted topic phrases are closest in meaning. Good examples: 'AI safety', 'EU AI Act regulation', 'GPU supply constraints', 'Theo Epstein on roster construction'. Distinct from `search_episodes`, which performs lexical keyword matching. | |
| show_guid | No | Optional canonical show GUID (as returned by `search_episodes` or `get_latest_episodes` in the `show_guid` field) to restrict topic search to a single podcast. Leave empty to search across all shows. | |
| published_after | No | Inclusive lower publication-date bound. Accepts YYYY-MM-DD or ISO 8601 datetime. | |
| published_before | No | Inclusive upper publication-date bound. Accepts YYYY-MM-DD or ISO 8601 datetime. |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | Number of episodes returned. |
| query | Yes | The topic query that was embedded and searched. |
| episodes | Yes | Episodes ranked by best topic-phrase similarity to the query. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds behavioral context: the server embeds the query string and finds episodes with closest meaning, and returns ranked results with matched topic phrases. No contradictions. Could mention if results are cached or if there are rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two main sentences plus a usage note) and well-structured. It front-loads the purpose, then explains when to use it, and ends with behavioral details. Every sentence is informative with no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of semantic search, the description thoroughly explains the difference from lexical search and tells the agent when to use each. An output schema exists (not shown but noted), so return values are covered. For a search tool, this is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with all parameters described. The description adds value by explaining the `topic` parameter's semantic nature with good examples and contrasting with `search_episodes`. Other parameters like `show_guid` reference other tools for clarity. Additional value beyond schema warrants a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Semantic topic search across the podcast catalog' and contrasts with the sibling tool `search_episodes` which does lexical matching. It provides concrete examples like 'AI safety' matching 'AI alignment', making the purpose precise and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on when to use this tool versus `search_episodes`: 'Best for conceptual or thematic queries — use `search_episodes` instead when the user is looking for a specific person, product, or verbatim phrase.' Also explains that it returns matched topic phrases to explain relevance before fetching transcripts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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