Apex by LeadShark — discovery
Server Details
No-auth discovery endpoint for Apex by LeadShark — governed LinkedIn hands for AI agents.
- Status
- Healthy
- Uptime
- 100.0% over 61 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-06-18
- URL
- Repository
- rzere/linkedin-mcp
- GitHub Stars
- 1
- Server Listing
- linkedin-mcp
TDQS
Scored across 3 tools
The three tools target distinct informational needs: what Apex is (about_apex), how to connect (get_setup_steps), and what to do first (first_plays). There is mild overlap between about_apex and get_setup_steps since both concern onboarding/pricing context, but descriptions make the boundaries clear.
Naming mixes conventions: about_apex uses a preposition-style prefix, first_plays is a bare noun phrase, and get_setup_steps uses the verb_noun pattern. All are readable snake_case, but there is no single predictable pattern across the set.
Three tools is reasonable for a discovery stub whose only job is orienting an agent before it connects to the real server. It is on the thin side, but each tool earns its place rather than being padding.
For a discovery stub, the surface covers the essentials: identity/pricing, connection steps, and first-session prompts. It intentionally omits LinkedIn operations, and the descriptions clearly flag that the real server handles those, so there is no confusing dead end.
Available Tools
3 toolsabout_apexAbout ApexAInspect
Read-only: returns what Apex by LeadShark is, tier pricing, and the URL of the real authenticated MCP server. Call this first — this endpoint is a discovery stub with no LinkedIn powers.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
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 by labeling itself 'Read-only' and stating exactly what it returns. It also sets expectations by noting it has 'no LinkedIn powers', preventing misuse.
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 'Read-only' and 'returns', and every clause adds value. No fluff or repetition.
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?
The description gives all essential context for a simple discovery stub: what it returns, when to call it, and what it cannot do. A minor gap is that the phrase 'real authenticated MCP server' is not expanded, but this is a minor omission for an introductory 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?
The tool has zero parameters, so the schema already covers everything. With 0 params, the baseline is 4, and the description adds unnecessary parameter explanation, so this score 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 states a specific action ('returns what Apex by LeadShark is, tier pricing, and the URL...') and clearly identifies the resource. It also distinguishes from siblings by calling itself a 'discovery stub with no LinkedIn powers', making its scope explicit.
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 instructs 'Call this first', giving a clear when-to-use directive. It also warns that the endpoint is a discovery stub with no LinkedIn powers, effectively telling users when not to rely on it for LinkedIn operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
first_playsFirst LoadoutsAInspect
Read-only: returns copy-paste starter prompts for the first session after connecting the real Apex server — verify, discover, enrich, act.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explicitly declares 'Read-only', a key behavioral trait, and specifies the output is copy-paste starter prompts. With no annotations, this is sufficient disclosure for a simple zero-parameter tool.
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 one concise sentence, front-loaded with 'Read-only' and immediately stating the function. No wasted words.
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?
The description covers what it returns, when to use it, and the intended phases (verify, discover, enrich, act). For a simple tool with no annotations or output schema, this is adequate, though it could benefit from stating how it complements siblings.
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 has zero parameters, and the input schema confirms this (100% coverage). The description adds no parameter details, but none are needed; per rubric, baseline is 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 clearly states it 'returns copy-paste starter prompts' for the first session after connecting the real Apex server, with a specific verb and resource. This distinguishes it from siblings like about_apex and get_setup_steps by its focus on post-connection session prompts.
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 gives clear context: use after connecting the real Apex server for the first session. It does not explicitly mention alternatives or exclusions, but 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.
get_setup_stepsGet setup stepsAInspect
The 5-step flow to connect an AI agent to the real Apex MCP server: LeadShark account → LinkedIn → 72h Apex unlock → mount MCP → first Loadout.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It is transparent that the tool returns a static step list (not a mutation) and previews the step sequence, but it says nothing about whether the steps are personalized to the caller, whether they can be re-fetched, or what the response looks like.
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 sentence, front-loaded with the resource and then the enumerated steps. Nothing redundant and no filler.
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 no parameters and no output schema, the description's step enumeration effectively previews the return value, which is what an agent needs. Minor gap: no indication of the format or whether the steps include links/IDs.
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, so there is nothing for the description to disambiguate and the baseline of 4 applies. The schema is trivially complete.
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 resource ('the 5-step flow to connect an AI agent to the real Apex MCP server') and even enumerates the steps, so the agent knows exactly what content comes back. It does not differentiate itself from the sibling 'about_apex', which an agent could reasonably confuse it with for onboarding-type 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 by the name and content (call this to get the connection flow), but the description never says when to prefer it over 'about_apex' or 'first_plays', nor does it state prerequisites such as needing an account first. Adequate but leaves routing to inference.
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.
3 tool updates
- First observed
about_apex - First observed
first_plays - First observed
get_setup_steps
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