Entra.Chat Podcast MCP Server

Server Quality Checklist

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Latest release: v0.1.4
Disambiguation4/5
Tools are mostly distinct: search, list, get, and find cover different actions. There is slight overlap between search_entra_podcasts (general transcript search) and find_tool_mentions (specific to tool mentions), but descriptions are clear enough to prevent confusion.
Naming Consistency5/5
All tools follow a consistent verb_noun snake_case pattern (search_entra_podcasts, get_episode, list_episodes, list_guests, get_guest, find_tool_mentions). The naming is uniform and predictable.
Tool Count5/5
Six tools is well-scoped for a podcast server covering search, episode browsing/retrieval, guest browsing/retrieval, and special tool-mention search. Each tool earns its place without unnecessary bloat.
Completeness5/5
The read-only domain of podcast transcripts and guest metadata is fully covered: list and get for episodes and guests, general search, and a niche search for tool mentions. No obvious gaps for the server's stated purpose.
Average 4.1/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 10 commits in the last 12 weeks
- Last stable release on August 19, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden; it discloses return content (metadata and transcript) and lookup keys. However, it doesn't mention behavior when no parameter or multiple parameters are provided, nor any error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One dense sentence, front-loaded with the verb and object, with no filler or redundant repetition of schema content.
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?
Effectively describes the return payload (guests, chapters, transcript timestamps) despite lacking an output schema. Missing edge-case behavior for optional parameters, but adequate for a straightforward lookup tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters have descriptions in the schema, so the baseline is 3. The description only restates lookup-by labels and adds no new syntax or relationship details beyond the schema.
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?
Clearly identifies tool as retrieving a specific Entra.Chat episode by three possible identifiers. The phrase 'specific episode' distinguishes it from sibling list/search tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies use for targeted lookups by video ID, episode number, or date, but does not explicitly name alternatives or state when not to use it. No guidance on conflicting or preferred identifiers.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of explaining behavior. It discloses that partial names match, that returning guests show all their appearances, and enumerates the exact fields returned. It does not mention error handling or auth, but the read-only nature is clear from 'Get'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single focused sentence that front-loads the core purpose before detailing the return contents. Every clause adds useful information, with no filler or redundancy.
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 one-parameter lookup with no output schema, the description does a good job of specifying the return structure: profile links and episode details (number, title, date, URL). It omits edge-case behavior like multiple partial matches, but overall it gives an agent enough context to understand what the tool returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes the 'name' parameter well (case-insensitive, partial names match), and the description mostly restates this. High schema coverage means the description adds little beyond what is already in the input schema, so the baseline score of 3 applies.
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 opens with a specific verb and resource: 'Get a specific Entra.Chat guest by name.' It clearly distinguishes this from sibling tools like list_guests or get_episode by focusing on a single guest and describing the exact return payload (profile links and episode appearances).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for targeted guest lookups ('specific guest by name') and notes that partial names match, but it does not explicitly contrast with alternatives such as list_guests or search_entra_podcasts. There is no when-to-use or when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the return fields (episode number, title, date, duration, guests, URL) and filter options, implying a read-only browse operation. However, it doesn't mention ordering, pagination behavior, or default response size beyond what the schema already documents.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences that are front-loaded with the core purpose, followed by return fields and a clear usage directive. Every sentence earns its place with no redundancy.
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 low-complexity listing tool with no output schema, the description covers purpose, return fields, filtering, and usage context relative to siblings. It could mention sort order or default behavior, but the schema covers limit/offset, making it sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description mentions year/month/guest filtering, which matches schema fields, but adds no extra semantics beyond what the schema already provides for each parameter.
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 ('Browse') and clearly identifies the resource ('Entra.Chat episode archive'), with optional filtering by year/month/guest. It distinguishes itself from siblings by explicitly positioning it as a discovery tool before using get_episode or search_entra_podcasts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool: 'Use this to discover what episodes exist before using get_episode or search_entra_podcasts.' It gives a clear context and names the primary alternatives, though it doesn't detail when not to use it (e.g., for full-text search).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the read-only nature ('Find', 'Returns') and specifies the output content (tool names, episode references, YouTube links). It does not mention pagination or ordering, but for a simple lookup tool this is adequate and adds value beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core purpose and return value, with no filler. Every phrase adds value, and the optional filter is mentioned succinctly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter search tool with no output schema, the description fully explains what to expect: results include tool names, episodes, and timestamped YouTube links. It is self-contained and sufficient for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both limit and query fully documented, so the description does not need to compensate. The description only reiterates the optional keyword filter, adding no extra semantic detail beyond the schema examples.
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 ('Find') with a clear resource ('community tools and open-source projects discussed on Entra.Chat episodes') and explicitly states what it returns (tool names, episodes, timestamped links). This differentiates it from sibling tools like search_entra_podcasts, which likely handle broader podcast search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: to locate tool mentions across episodes, with an optional keyword filter. It does not explicitly name alternatives or exclusions, but the purpose is distinct enough that an agent can infer when to select it over siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly explains what the tool returns and implies a read-only nature via 'Browse.' It also indicates the tool does not provide full episode lists, directing to get_guest for that. The description does not explicitly mention side effects, but for a directory listing tool, the behavior is well-understood and clearly described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, each earning its place. The first sentence states the purpose, the second details the return contents, and the third provides a pointer to an alternative. It is front-loaded with the primary purpose and contains no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema, the description appropriately explains the return structure (profile links, episode count, latest appearance). It also covers the tool's scope and directs users to a sibling tool for more detail. The input schema handles parameter documentation, and the description provides the necessary context for a listing tool. The tool is simple enough that this description is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description does not add any parameter-specific meaning beyond what the input schema already provides. The parameters (limit, query, offset) are fully described in the schema, and the description focuses on the return structure rather than parameter details. No additional value is added here.
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 clearly states the tool's purpose: 'Browse the directory of Entra.Chat podcast guests.' It specifies the resource (guest directory), the verb (browse), and the return structure (profile links, episode counts, latest appearance). It also distinguishes itself from the sibling tool get_guest by directing users there for full per-guest episode lists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool versus an alternative: 'Use get_guest for a full per-guest episode list.' It implies that this tool is for browsing the directory and getting summary information, and it gives a clear pointer for a more detailed need. However, it doesn't explicitly discuss other siblings like search_entra_podcasts or list_episodes, but the context is sufficient for most use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does well: it discloses the hybrid fusion algorithm (Reciprocal Rank Fusion), the external dependency (OPENAI_API_KEY), and the nature of responses (excerpts, metadata, deep links). It does not cover fallback behavior when the API key is missing or any error/rate-limit behavior, but for a read-only search tool this is acceptable transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, no fluff. The first sentence states the action and resource, the second describes the return values and search algorithms, and the third provides configuration guidance. Every sentence contributes, and key information is front-loaded.
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?
The description covers the tool's purpose, output contents, mode behavior, and dependencies. It lacks a precise output schema (none provided) but gives enough detail that an agent can infer what to expect. It does not explicitly say it searches across all episodes, but that is implied. Overall, it is adequate for the tool's complexity.
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 coverage is 100%, so baseline is 3. The description adds real value by explaining what hybrid mode does (BM25 + semantic via RRF) and the API key requirement for semantic mode. This exceeds simple schema labels and helps the agent choose the right mode.
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 opens with 'Search transcripts of the Entra.Chat podcast' — a specific verb and resource. It clearly distinguishes from siblings (get_episode, list_episodes, list_guests, find_tool_mentions) by focusing on cross-transcript search. It also enumerates the output: excerpts, episode metadata, guest names, and timestamped deep links.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clarifies when to use this tool: for natural language or keyword search over transcripts. It explains the three modes (hybrid, semantic, keyword) and gives practical guidance — semantic requires OPENAI_API_KEY, keyword works with none. It does not explicitly contrast with sibling tools, but the purpose and sibling names imply the distinction.
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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