Social & Content MCP Server
Server Details
MCP server for social media and content data including social profiles, engagement metrics, content trends, and influencer analytics for AI agents.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4.2/5 across 4 of 4 tools scored.
Each tool targets a distinct platform (Steam, dev.to, Eventbrite, podcast directories) with no overlap in purpose or output. Agents can easily differentiate based on platform and content type.
Three tools use the 'search_' prefix, but one uses 'get_steam_games', breaking the pattern. While still readable, the inconsistency creates minor confusion about the expected verb.
With 4 tools, the server is focused and each tool serves a clear purpose. The count is slightly low but appropriate for a narrow selection of platforms, avoiding bloat.
Given the server's broad title 'Social & Content MCP Server', it lacks coverage of major platforms like YouTube, Twitter, Reddit, or general RSS feed support. The tool surface has significant gaps for the implied domain.
Available Tools
4 toolsget_steam_gamesARead-onlyInspect
Search Steam game platform for video games by title or keyword. Returns game name, price in USD, average user rating, review count, release date, and Steam store page URL. Use for game discovery, price monitoring, or review research before purchase.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Game title or genre search (e.g. 'Elden Ring', 'strategy games', 'indie puzzle') | |
| max_results | No | Number of game results to return (default 10) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds context about what the tool searches and returns, with no contradictory or hidden traits.
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?
Three sentences, front-loaded with the action, no wasted words. All information is relevant and efficiently presented.
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 simple two-parameter tool with no output schema, the description adequately explains purpose, parameters, and return fields. Missing potential details like pagination or rate limits, but overall complete for typical use.
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 baseline is 3. Description adds minimal extra meaning beyond the schema, e.g., 'by title or keyword' aligns with query description, but no additional format or constraints are mentioned.
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 searches Steam for games by title or keyword, and specifies the returned fields. Sibling tools are for different platforms (dev.to, events, podcasts), so differentiation is clear.
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 explicitly mentions use cases: game discovery, price monitoring, review research. It does not state when not to use, but given sibling tools are unrelated, the context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_devtoARead-onlyInspect
Search dev.to platform for developer articles, tutorials, and technical posts. Returns article title, author, read time, publication date, tags, and direct link. Use for learning new dev topics, finding tutorials, or staying updated on developer community trends.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search keywords for developer content (e.g. 'React tutorial', 'Docker basics', 'TypeScript patterns') | |
| max_results | No | Number of articles to return (default 10, good for recent content) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint. The description adds return field details (title, author, etc.) but does not mention rate limits, pagination, or other behaviors. No contradiction with annotations.
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?
Three sentences, clear and front-loaded with the tool's core purpose. Efficiently communicates key information without extraneous text.
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 simple search tool with 2 parameters and no output schema, the description adequately covers functionality and return values. Could mention default handling of max_results but is sufficient.
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 both parameters described. The description adds no additional parameter semantics beyond the schema's field descriptions. 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 it searches dev.to for articles, tutorials, and technical posts, listing return fields like title, author, read time, etc. It distinguishes from sibling tools like get_steam_games, search_events, and search_podcasts by platform and content type.
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 provides explicit use cases: 'learning new dev topics, finding tutorials, staying updated.' While it does not explicitly state when not to use or compare with alternatives, the sibling tools are in different domains, making usage context clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_eventsARead-onlyInspect
Search Eventbrite for upcoming local and online events by topic and location. Returns event name, date/time, location, ticket price, event description, and registration URL. Use for event discovery, community involvement, or entertainment planning.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Event type or topic to find (e.g. 'tech conference', 'comedy show', 'food festival') | |
| location | No | City or region to search for events (e.g. 'New York, NY', 'Los Angeles', 'virtual') |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and openWorldHint=true. Description adds context about return fields and the purpose (upcoming events, registration URL). No contradictions; adds useful behavioral context beyond annotations.
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: first defines action and inputs, second lists outputs and use cases. No wasted words; front-loaded with key information. Highly efficient.
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?
Covers inputs, outputs, and use cases adequately for a 2-param search tool with no output schema. Does not detail formatting of dates/prices, but that is acceptable for discovery.
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 has 100% coverage with descriptions for both query and location. Description repeats similar info but adds context (e.g., 'City or region' in schema is reinforced). Minimal additional meaning beyond what schema already 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 it searches Eventbrite for events by topic and location, listing return fields (name, date/time, location, price, description, registration URL). Distinguishes from sibling tools like search_podcasts and search_devto, which serve different domains.
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 states use cases (event discovery, community involvement, entertainment planning). Does not provide explicit when-not-to-use or alternatives, but sibling tools are clearly differentiated by domain, making misuse unlikely.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_podcastsARead-onlyInspect
Search podcast directories for episodes matching topics or keywords. Returns episode title, podcast name, description, episode length, publish date, and streaming link. Use for podcast discovery, topic research, or building listening playlists.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Podcast topic or search terms (e.g. 'technology news', 'business interviews', 'science explanations') | |
| max_results | No | Number of podcast episodes to retrieve (default 10) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. Description adds return field listing but lacks details on pagination, rate limits, or scope limitations. Adequate but not enhanced beyond annotations.
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, front-loaded with action and returns, then use cases. Every sentence adds value with no waste.
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 low complexity (2 params, no output schema, read-only), the description fully covers what the tool does, returns, and when to use it.
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 both parameters with descriptions. Description does not add new meaning beyond echoing 'topics or keywords'. Baseline score of 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 uses specific verbs ('Search', 'Returns') and identifies the resource ('podcast directories', 'episodes'). It clearly distinguishes from sibling tools which cover games, dev articles, and events.
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 lists use cases ('podcast discovery, topic research, building playlists') but does not provide when-not-to-use or refer to alternatives. Sibling tools are unrelated, so implicit differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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