# Workopia — Job Search (remote · workopia.io)

Search 6.3M+ live jobs from companies' own career pages, plus resume tailoring & cover letters.

- Trust score: 60/100 (medium)
- Change this week: +5
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- remote · `workopia.io`: 60/100 (this document), [markdown](https://verifymcp.io/servers/workopia-workopia-mcp/api-mcp-jobs.md), [page](https://verifymcp.io/servers/workopia-workopia-mcp/api-mcp-jobs)

## Channel facts

- Endpoint: `https://workopia.io/api/mcp-jobs`
- Transports: `streamable-http`
- Auth: `none`
- Version: `1.0.2`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-03.

- **Endpoint Security**: 63/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - Authorisation check failed: no authorisation is required to call this server, and it exposes a tool marked destructive (tailor_resume_tool).
  - HTTPS is enforced; there's no plaintext access path.
  - The HSTS (Strict-Transport-Security) header is present.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 43/100
  - AI-judged instruction clarity (good).
  - Context-footprint check failed: tool/resource definitions use about 3111 tokens (~622/item across 5 items; 5 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 27/100
  - Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 87/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 60% of tool parameters carry a description.
- **Capabilities**: 60/100
  - Spec-recency check failed: implements MCP spec 2025-06-18; the latest is 2026-07-28.

## Install

### Claude

```bash
claude mcp add --transport http workopia-workopia-mcp https://workopia.io/api/mcp-jobs
```

### Codex

```toml
[mcp_servers.workopia-workopia-mcp]
url = "https://workopia.io/api/mcp-jobs"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "workopia-workopia-mcp": {
      "type": "remote",
      "url": "https://workopia.io/api/mcp-jobs",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add workopia-workopia-mcp --url https://workopia.io/api/mcp-jobs --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  workopia-workopia-mcp:
    url: "https://workopia.io/api/mcp-jobs"
```

### Other

```json
{
  "mcpServers": {
    "workopia-workopia-mcp": {
      "type": "http",
      "url": "https://workopia.io/api/mcp-jobs"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-03 (score 60, +1)

No change was recorded against any check on this day. Stability & Change Management went from 23 to 27. That category is still filling its 30-day observation window: 7 days of observed history at the previous scan, 8 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-08-01 (score 59, +1)

No change was recorded against any check on this day. Stability & Change Management went from 17 to 20. That category is still filling its 30-day observation window: 5 days of observed history at the previous scan, 6 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-31 (score 58, +1)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-29 (score 57, +1)

No change was recorded against any check on this day. Stability & Change Management went from 7 to 10. That category is still filling its 30-day observation window: 2 days of observed history at the previous scan, 3 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-28 (score 56, +1)

No change was recorded against any check on this day. Stability & Change Management went from 3 to 7. That category is still filling its 30-day observation window: 1 days of observed history at the previous scan, 2 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-27 (score 55, 0)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-26 (score 55)

First indexed and scored.

## MCP tools (5)

### `tailor_resume_tool` (~760 tokens)

Tailor a resume to a SPECIFIC job — TWO steps. STEP 1 (default; action omitted or 'prepare'): the server returns the job's full JD, its must-have skills/requirements, and the candidate's current resume, plus tailoring instructions. YOU (the model) then WRITE the tailored resume as JSON Resume, following the instructions — weave JD keywords into existing bullets only where the candidate genuinely has the experience, never fabricate experience/titles/dates/employers, keep all dates and company names, and flag any keyword you couldn't honestly add. STEP 2: call this tool again with action:'save', tailored_resume:<your JSON Resume>, and job_id — the server renders a PDF and saves it to the candidate's Workopia dashboard (requires sign-in). Use whenever the user references a specific job to tailor for: 'tailor for #1', 'for Morgan Stanley', 'tailor my resume for this role: <JD>'. Resolving job_id (same rules as job_detail_tool): from the most recent prior search/refine result — (a) numeric/ordinal → the Nth job; (b) company name → Company-field match; (c) role/title phrase → Job-Title match — then pass that job's **Job Id** value VERBATIM. Do NOT use placeholders like 'JOB_1' or '#1'. For STEP 1 supply ONE of job_id (preferred — server fetches the JD from Mongo) OR job_description, plus the candidate's resume via resume_text / resume_content / resume_data. For general 'improve my resume' (no specific job), do NOT call this tool — call resume_tool action=improve instead. Note: the tailored resume is written by your AI client's own model — the assistant you are already using — so it works out of the box with nothing to configure; Workopia runs no LLM of its own and never charges for the AI.

Input parameters:

- `action` (string): Omit or 'prepare' = STEP 1 (server returns JD + resume + instructions for you to tailor). 'save' = STEP 2 (pass tailored_resume; server renders a PDF and saves it to the dashboard; requires sign-in).
- `company` (string)
- `customization_level` (string)
- `job_description` (string): Full JD text when the user pastes it directly (alternative to job_id).
- `job_id` (string): ID of a job from a prior search/refine result. Use the **Job Id** value from the prior search result's content text VERBATIM. Server fetches full JD from Mongo.
- `job_title` (string)
- `parameters` (object)
- `resume_content` (string)
- `resume_data` (object): PREFERRED shape — structured resume per utils/tailor/types.ts ResumeTree. Server, widget, and main-site PDF template all consume this exact shape. Collect these fields from the user before calling wh…
- `resume_text` (string): User's resume content (plain text or JSON Resume as string). Fallback when resume_data is not provided.
- `session_id` (string)
- `tailor_resume` (object): Optional wrapper containing the same fields above (legacy shape).
- `tailored_resume` (object): STEP 2 only: the tailored resume you generated, as a JSON Resume object (or a JSON string). The server renders it to PDF and stores it on profile.applications[job_id].resumeTailor.
- `user_email` (string)
- `user_profile` (object): Optional main-site profile object; used as a fallback source for name/title/contact/experience when resume_data and resume_text are both absent.

### `cover_letter_tool` (~613 tokens)

Write a cover letter for a SPECIFIC job — TWO steps. STEP 1 (default; action omitted or 'prepare'): the server returns the job's JD and the candidate's background, plus writing instructions. YOU (the model) then WRITE the cover letter (250–350 words, specific to the role, mapping the candidate's real achievements to the JD — never fabricate). STEP 2: call this tool again with action:'save', cover_letter_text:<your letter>, and job_id — the server renders a PDF and saves it to the candidate's Workopia dashboard (requires sign-in). Use whenever the user asks for a cover letter for a specific job. Resolving job_id (same rules as tailor_resume_tool / job_detail_tool): pass the **Job Id** value from the most recent prior search/refine result VERBATIM; no placeholders like 'JOB_1' or '#1'. For STEP 1 supply ONE of job_id (preferred — server fetches the JD from Mongo) OR job_description, plus the candidate's resume via resume_text / resume_content / json_resume / user_profile.

Input parameters:

- `action` (string): Omit or 'prepare' = STEP 1 (server returns JD + background + instructions for you to write). 'save' = STEP 2 (pass cover_letter_text; server renders a PDF and saves it to the dashboard; requires sign…
- `company` (string): Optional; used in the confirmation line.
- `cover_letter` (object): Optional wrapper containing the same fields above (legacy shape).
- `cover_letter_text` (string): STEP 2 only: the cover letter you wrote (plain text). The server renders it to PDF and stores it on profile.applications[job_id].coverLetter.
- `job_description` (string): Full JD text when the user pastes it directly (alternative to job_id).
- `job_id` (string): ID of a job from a prior search/refine result. Use the **Job Id** value from the prior search result's content text VERBATIM. Server fetches full JD from Mongo.
- `job_title` (string): Optional; used in the 'for <role> at <company>' confirmation line.
- `json_resume` (object): Optional JSON Resume object (basics/work/skills). Takes precedence over resume_text when both present.
- `parameters` (object)
- `resume_content` (string)
- `resume_text` (string): User's resume content (plain text or JSON Resume as string).
- `session_id` (string)
- `user_email` (string): If provided, server fetches the full Workopia profile for the cover letter header + writes the generated cover letter back to profile.applications[jobId].coverLetter.
- `user_profile` (object): Optional main-site profile object; used as a fallback source for summary/skills/experience and for the cover letter header (firstName, lastName, email, phone, city, country).

### `job_tool` (~1237 tokens)

Search jobs across 90+ countries by title, location, salary, remote/hybrid work mode, or employment type. Find roles in tech, finance, product, design, marketing, and every other vertical — aggregated from 1000+ ATS sources globally. Default action is search; use refine when the user asks for more matches or gives feedback on a prior result set; use save to bookmark a job for the signed-in user (requires OAuth). REFINE PROTOCOL (action=refine has THREE distinct modes): (1) Pure continuation / 'show me more' / 'next batch' / 'another set' / 'more like these': pass refine_recommendations.exclude_ids = the full array of **Job Id** values from the most recent search/refine result's content text (verbatim) + refine_recommendations.session_id = prior response's session_id if present. Server returns next 10 unique jobs. (2) 'Show me more like #N' / 'similar to the Atlassian one' / 'jobs like #2': pass refine_recommendations.liked_indexes = [N] (1-based position from prior numbered list) + exclude_ids + session_id. Equivalently you may pass refine_recommendations.liked_job_ids = [<that job's **Job Id** value verbatim>]. Server seeds the recommendation from that job's title/skills/company profile. (3) 'Less like #N' / 'no more N-style jobs' / 'avoid jobs like that': pass refine_recommendations.disliked_indexes = [N] (or disliked_job_ids = [<Job Id>]) + exclude_ids + session_id. Server suppresses similar jobs. All three modes: if you skip exclude_ids, the user sees duplicates — that's a failure. The handler layers exclude_ids with server-side AgentKit memory, so partial lists still work. NEVER invent 'JOB_1' / '#1' as job_id values — always use the real **Job Id** string from the prior result's content text. For detail requests (user asks about a specific job from the list, e.g. 'details for #1', 'show me this job', 'tell me more about <company>'), DO NOT call this tool — call job_detail_tool instead. That separate tool binds to the job-detail widget card so the full job car…

Input parameters:

- `action` (string): Optional; omitted = search. refine = after results/feedback; save = bookmark a job for the signed-in user.
- `parameters` (object)
- `refine_recommendations` (object): Refine args. Pass exclude_ids (array of Job Id strings from prior result) and session_id always. For 'more like #N': pass liked_indexes=[N] or liked_job_ids=[<Job Id>]. For 'less like #N': pass disli…
- `save_job` (object): Save args. Required: job_id (from job_cards[].card.id in a prior search result). Optional: job_title, company, job_url.
- `search_jobs` (object): Search args. Required: city. Optional filters surface only when the user explicitly mentions them — omit otherwise. job_title+city uses indexed snapshot; company+city (optional job_title) uses legacy…

### `job_detail_tool` (~385 tokens)

Render the full job-detail card for a specific job the user asks about. Use this whenever the user references a particular job from a prior search result — by number (#1, '1', 'first', 'the 3rd one', 'job 3'), by company name (partial or full, e.g. 'Morgan Stanley', 'Morstan'), by role/title phrase ('the analyst role', 'the credit risk one'), or by any 'show me this job' / 'tell me more about X' / 'view this role' style request. Resolving job_id from user reference: identify the right job from the most recent prior search/refine result (the numbered list you generated): (a) numeric/ordinal → the Nth job; (b) company name → substring match on Company field; (c) role/title phrase → substring match on Job Title field. Then pass that job's **Job Id** value from the prior search result's content text VERBATIM as job_id. Do NOT use a placeholder like 'JOB_1', '#1', or any synthetic id — only the real **Job Id** string from the prior result is server-valid. Required: job_id. OUTPUT BEHAVIOR: Render the response as a structured markdown card with the job's title (linked to the apply URL), company, location, salary, employment type, work mode, must-have skills, key requirements, highlights, and summary. Follow it with a brief next-step hint (e.g. 'Want to save it, find similar roles, ask about the company, or tailor your resume for this role?').

Input parameters:

- `get_job_detail` (object)
- `job_id` (string): The id from a prior search result's job_cards[].card.id. Required.
- `parameters` (object)
- `user_email` (string)

### `dashboard_tool` (~116 tokens)

Show the signed-in user's Workopia dashboard (saved, tailored, and applied jobs + latest resume). Requires OAuth. Default action is list; optional status_filter (all | saved | tailored | applied). Use whenever the user asks to recall their Workopia activity: 'my applications', 'what jobs have I saved / applied to / tailored', 'show my dashboard', 'where did I leave off'. Returns a secure link to open the full dashboard on the web.

Input parameters:

- `action` (string)
- `status_filter` (string)

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/workopia-workopia-mcp/api-mcp-jobs#diagnostics

## Score history

- 2026-08-03: 60
- 2026-08-02: 59
- 2026-08-01: 59
- 2026-07-31: 58
- 2026-07-30: 57
- 2026-07-29: 57
- 2026-07-28: 56
- 2026-07-27: 55
- 2026-07-26: 55

## Links

- Remote endpoint: https://workopia.io/api/mcp-jobs
- Repository: https://github.com/workopia/workopia-mcp
- Changelog RSS feed: https://verifymcp.io/servers/workopia-workopia-mcp/api-mcp-jobs/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/workopia-workopia-mcp/api-mcp-jobs/changelog.json
- HTML version of this page: https://verifymcp.io/servers/workopia-workopia-mcp/api-mcp-jobs