Index Agentica
Server Details
Search a curated directory of agent tools, MCP servers, APIs, protocols, payments and skills. Tools: search, get_entry, get_content, list_categories.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
TDQS
Scored across 4 tools
search, get_entry, and get_content have overlapping retrieval purposes, and the distinction between entry and long-form content requires careful reading of descriptions and type parameters. get_content explicitly mentions skills as a type, overlapping with entry retrieval. list_categories is clearly distinct.
All tool names follow a consistent verb_noun pattern: get_content, get_entry, list_categories, search. search lacks a noun but is a common exception; overall naming is predictable and readable.
Four tools is on the thin side for a directory and long-form content server. A category browsing tool and a search/get split are present, but the surface feels minimal for the stated scope of entries, categories, guides, comparisons, stacks, and skills.
The server covers search and retrieval/browsing, but there are no write or CRUD operations, which is typical for a read-only directory. The content type coverage is reasonable but there are no dedicated tools for listing entries by category or retrieving multiple items, which could be limiting.
Available Tools
4 toolsget_contentGet guide, comparison, stack or skillARead-onlyIdempotentInspect
Fetch one Index Agentica long-form item by type and id (as returned by search). Returns its metadata (title, summary, author, tags, dates, referenced entries with links, related items, sources, links) and its markdown (scheme links resolved to absolute URLs). Comparisons include the structured table (criteria, one row per entry, verdict); stacks include the use case and components; skills include the full SKILL.md (skill_md) plus download links (links.zip, links.skill_md). Unknown ids return an error with suggestions.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Item id (kebab-case slug) as returned by search. | |
| type | Yes | guide, comparison, stack or skill. | |
| include_html | No | Also return the rendered HTML body. |
Output Schema
| Name | Required | Description |
|---|---|---|
| content | Yes | The item: front_matter, markdown, links and type-specific fields (comparison, stack, skill_md). See https://indexagentica.com/openapi.json (LongformItem). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, non-destructive, non-open-world. The description adds valuable behavioral context beyond annotations: it details the return payload by type (comparison table, stack components, skill SKILL.md and download links) and states that unknown ids return an error with suggestions. That's substantive transparency about output shape and failure modes that no structured field provides.
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?
One dense but well-structured paragraph front-loaded with purpose, then payload, then edge case. Every sentence earns its place, though the long parenthetical listing metadata fields is slightly heavy for a single breath.
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 a rich output schema exists, the description needn't explain every return field, yet it goes further by characterizing the shape per item type and the error case. It omits explicit guidance on when to prefer get_content over get_entry, which would complete the routing picture, but it is otherwise sufficient for correct invocation.
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 all three parameters are documented in the schema with descriptions and an enum. The description reinforces that type and id are the key inputs but adds no new syntax beyond what the schema already provides. Baseline 3 is appropriate when the schema does the heavy lifting.
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?
States a specific verb (Fetch), resource (Index Agentica long-form item), and the keying (by type and id as returned by search). The title and description together distinguish it from siblings like get_entry and 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?
Implies this is the follow-up to search by noting the id is 'as returned by search', and describes error behavior for unknown ids. It doesn't explicitly say when to use get_content vs get_entry, which would be useful given the sibling, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_entryGet directory entryARead-onlyIdempotentInspect
Fetch one Index Agentica entry by its id (kebab-case slug, e.g. "model-context-protocol"). Returns every field: name, category, summary, description, url, repo, docs, tags, license, pricing, status, agent_access (llms_txt, openapi, mcp_endpoint, auth), related ids, sources, dates and links. If the id is unknown the result is an error with suggested ids.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Entry id (kebab-case slug) as returned by search. |
Output Schema
| Name | Required | Description |
|---|---|---|
| entry | Yes | The full entry, following https://indexagentica.com/schema/entry.schema.json plus a links object. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds genuinely useful behavior: it returns the complete field set in a single call and returns an error with suggested ids for unknown ids, which tells the agent how failure manifests.
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 front-loaded sentences that state the operation first and details second. The long enumeration of returned fields is somewhat redundant given an output schema exists, but it does not obscure the core instruction.
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?
For a single-parameter read with full annotations and an output schema, the description covers the identifier format, the success shape, and the failure mode. Nothing needed to invoke or interpret the call is missing.
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 the pattern plus maxLength fully constrain the single id parameter, so the schema does the heavy lifting. The description reinforces it with a kebab-case example ('model-context-protocol') but adds no semantics beyond the schema's own description.
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?
States a specific verb and resource ('Fetch one Index Agentica entry by its id') and pins the identifier format with a concrete example. It is clearly distinguishable from siblings like search (which finds ids), list_categories, and get_content.
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?
Usage is implied rather than stated: the id must come from a prior search, and the mention of an error with suggested ids hints at a recovery flow. It never explicitly says 'use search first' or contrasts itself with get_content, so the agent must infer the routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_categoriesList categoriesARead-onlyIdempotentInspect
List all Index Agentica categories with their slug, name, description, entry count and links (HTML page and JSON). Use a slug as the category filter for search.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| total | Yes | Total number of entries in the directory. |
| generated | No | When the published index was built. |
| categories | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered structurally. The description adds little beyond this, and its field list largely duplicates the existing output schema, leaving the bar for extra behavioral context only partially met.
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 sentences, no filler, with the resource scope front-loaded before the chaining instruction. Every clause carries information an agent can act on.
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?
For a zero-parameter read tool with annotations and an output schema, the description supplies everything needed to select and invoke it. Absent details such as ordering or pagination are minor given the small, bounded nature of a category listing.
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?
The tool takes zero parameters, which sets the baseline at 4. The only parameter-like mention (slug) is a value consumed by a different tool, not an input here, so there is nothing further to clarify.
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?
States a precise verb and resource ("List all Index Agentica categories") and enumerates the returned fields (slug, name, description, entry count, links), so the agent knows exactly what it gets. The tie-in to search via slug also implicitly separates it from get_content/get_entry/search, which operate on entries, not categories.
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 tells the agent how to chain this tool with search ("Use a slug as the category filter for search"), which is real when-to-use guidance. It does not state any when-not conditions or name the sibling tools directly, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
searchSearch Index AgenticaARead-onlyIdempotentInspect
Search Index Agentica: the directory of agent-usable resources (skills, harnesses, MCP servers, tools, protocols, APIs, information sources, finance/payments, directories) plus its long-form content (guides, comparisons, stacks and downloadable Agent Skills). Matches the query words against name/title, id, tags, summary and description and returns the best matches first, each with its type, a relevance score and links (HTML, markdown, JSON). Optionally filter by type (entry, guide, comparison, stack, skill; default all), category (entries only) and/or tags (ALL given tags must match). An empty query with a filter lists everything in that filter. For full details use get_entry for type entry, or get_content with the type and id for long-form items.
| Name | Required | Description | Default |
|---|---|---|---|
| tags | No | Optional list of tag slugs; results must have all of them (e.g. ["open-source", "python"]). | |
| type | No | Optional result type: entry (directory entries), guide, comparison, stack, skill, or all (default). | all |
| limit | No | Maximum number of results (1-50, default 10). | |
| query | No | Free-text search words, e.g. "browser automation" or "payments x402". May be empty when category or tags are given. | |
| category | No | Optional entry category slug to restrict results to (implies type entry). Current categories: skills, harnesses, mcp-servers, tools, protocols, apis, information, finance-payments, directories, infrastructure, evals-observability. |
Output Schema
| Name | Required | Description |
|---|---|---|
| tags | No | |
| type | No | Type filter applied (all when none). |
| limit | No | |
| query | Yes | |
| total | Yes | Number of matches before the limit was applied. |
| results | Yes | |
| category | No | Category filter applied (omitted when none). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds real behavioral context beyond that: which fields are matched, that results are ranked best-first, and that each result carries type, relevance score and links. It does not cover pagination or result-count behavior, but the added matching/ranking details are substantive.
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?
A single dense paragraph that front-loads the resource scope, then matching behavior, then filters, then the sibling hand-off. All sentences carry information, though the opening inventory of content types is slightly list-heavy.
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?
With an output schema present, return-value details are not required, and the description still notes the shape (type, relevance score, links). Combined with full schema coverage and annotations, an agent has everything needed to call it 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%, so the baseline is 3, but the description adds semantics the schema does not: tags require ALL given tags to match, category implies type entry, and an empty query plus a filter lists everything in that filter. These are non-obvious interaction rules that earn a bump above baseline.
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?
States a specific verb (search) and resource (the Agentica index of agent-usable resources and long-form content), and enumerates what is searched over. It is clearly distinguishable from the get_* siblings, which it names explicitly.
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 routes the agent: use get_entry for type entry and get_content with type+id for long-form items when full details are needed. It also documents the edge case of an empty query with a filter, which is genuine when-to-use guidance.
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.
4 tool updates
- First observed
get_content - First observed
get_entry - First observed
list_categories - First observed
search
Related MCP Servers
- AlicenseAqualityCmaintenanceEnables brand visibility monitoring across major AI platforms like ChatGPT, Claude, Gemini, and Perplexity. It allows users to track visibility scores, analyze competitor data, and receive actionable insights to improve AI-generated brand recommendations.1622 npm1MIT
- AlicenseCqualityBmaintenanceCompetitor Monitor AI - MCP server providing AI-powered tools and automation by MEOK AI Labs1114 npm40 PyPIMIT
- AlicenseAqualityCmaintenanceRevnuvo Company Intelligence tells AI agents what changed at a company, with evidence. It observes company websites, technologies, and DNS over time and returns timestamped, confidence-aware changes, signals, and monitoring.9MIT

industrylens-mcpofficial
AlicenseNot gradedqualityBmaintenanceBrowse IndustryLens's published competitive-intelligence reports and head-to-head competitor comparisons from any AI agent — real, source-backed data.MIT
Glama MCP Gateway
Add one secure layer between your agents and this server.