Freelance MCP Server

search_gigs

Find freelance gigs by skills, budget, project type, and platform. Filter opportunities to match your criteria before pitching.

Instructions

Search for freelance gigs based on skills and criteria

Args:
    skills: List of skills to match against
    max_budget: Maximum budget/rate to filter by
    min_budget: Minimum budget/rate to filter by
    project_type: Type of project (fixed_price, hourly, retainer, contest)
    platforms: List of platforms to search (upwork, freelancer, etc.)
    use_real_api: Use real API integration (True) or mock data (False)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "skills": "<skills>"
    },
    "name": "search_gigs"
  }
}

Input Schema

Name	Required	Description	Default
`skills`	Yes
`platforms`	No
`max_budget`	No
`min_budget`	No
`project_type`	No
`use_real_api`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.1.0Sep 13, 2026

TDQS

C2.9/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden, yet it discloses almost nothing: not whether this hits external APIs, what the rate/quota behavior is, whether the mock-data path affects results predictably, or what happens on empty matches. The one genuine disclosure is the use_real_api real-vs-mock toggle, which is real context but far from sufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose line is front-loaded and the arg list is easy to scan, but much of it merely echoes the schema's own property titles (skills, max_budget, min_budget, platforms) instead of adding information, and the 'Args:' docstring format is not the most compact.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The output schema exists, so return values need not be described, and all six inputs are at least named. But for a six-parameter, annotation-free search tool that reaches external platforms, the description leaves usage context, matching semantics, and safety/behavioral details unstated.

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 0%, so the description must compensate, and it does list every parameter with a terse gloss, including the project_type values and platform examples. However, it omits units/currency for budgets, matching semantics for skills (AND vs OR), and the default/effect of use_real_api beyond a one-line restatement.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a clear verb+resource: 'Search for freelance gigs based on skills and criteria'. It is specific about what is searched, but it does nothing to distinguish itself from siblings like get_smart_recommendations or analyze_skill_demand, so an agent gets no routing help.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance, no prerequisites, and no mention of any alternative tool. The only contextual hint is the implicit 'search' framing, which does not tell an agent when this beats the recommendation or analysis siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server