feat(tools): add search_people tool

AGENTS.md

@@ -61,6 +61,7 @@ This is a **LinkedIn MCP (Model Context Protocol) Server** that enables AI assis
 | `get_job_details` | Get job posting details |
 | `search_jobs` | Search jobs by keywords and location |
 | `close_session` | Close browser session and clean up resources |
+| `search_people` | Search for people by keywords and location |
 
 **Tool Return Format:**
 

README.md

@@ -44,6 +44,7 @@ What has Anthropic been posting about recently? https://www.linkedin.com/company
 | `get_company_profile` | Extract company information with explicit section selection (posts, jobs) | Working |
 | `get_company_posts` | Get recent posts from a company's LinkedIn feed | Working |
 | `search_jobs` | Search for jobs with keywords and location filters | Working |
+| `search_people` | Search for people by keywords and location | Working |
 | `get_job_details` | Get detailed information about a specific job posting | Working |
 | `close_session` | Close browser session and clean up resources | Working |
 

docs/docker-hub.md

@@ -8,6 +8,7 @@ A Model Context Protocol (MCP) server that connects AI assistants to LinkedIn. A
 - **Company Profiles**: Extract comprehensive company data
 - **Job Details**: Retrieve job posting information
 - **Job Search**: Search for jobs with keywords and location filters
+- **People Search**: Search for people by keywords and location
 - **Company Posts**: Get recent posts from a company's LinkedIn feed
 
 ## Quick Start

linkedin_mcp_server/scraping/extractor.py

@@ -383,3 +383,31 @@ async def search_jobs(
             "pages_visited": [url],
             "sections_requested": ["search_results"],
         }
+
+    async def search_people(
+        self,
+        keywords: str,
+        location: str | None = None,
+    ) -> dict[str, Any]:
+        """Search for people and extract the results page.
+
+        Returns:
+            {url, sections: {name: text}, pages_visited, sections_requested}
+        """
+        params = f"keywords={quote_plus(keywords)}"
+        if location:
+            params += f"&location={quote_plus(location)}"
+
+        url = f"https://www.linkedin.com/search/results/people/?{params}"
+        text = await self.extract_page(url)
+
+        sections: dict[str, str] = {}
+        if text:
+            sections["search_results"] = text
+
+        return {
+            "url": url,
+            "sections": sections,
+            "pages_visited": [url],
+            "sections_requested": ["search_results"],
+        }

linkedin_mcp_server/tools/person.py

@@ -83,3 +83,53 @@ async def get_person_profile(
 
         except Exception as e:
             return handle_tool_error(e, "get_person_profile")
+
+    @mcp.tool(
+        annotations=ToolAnnotations(
+            title="Search People",
+            readOnlyHint=True,
+            destructiveHint=False,
+            openWorldHint=True,
+        )
+    )
+    async def search_people(
+        keywords: str,
+        ctx: Context,
+        location: str | None = None,
+    ) -> dict[str, Any]:
+        """
+        Search for people on LinkedIn.
+
+        Args:
+            keywords: Search keywords (e.g., "software engineer", "recruiter at Google")
+            ctx: FastMCP context for progress reporting
+            location: Optional location filter (e.g., "New York", "Remote")
+
+        Returns:
+            Dict with url, sections (name -> raw text), pages_visited, and sections_requested.
+            The LLM should parse the raw text to extract individual people and their profiles.
+        """
+        try:
+            await ensure_authenticated()
+
+            logger.info(
+                "Searching people: keywords='%s', location='%s'",
+                keywords,
+                location,
+            )
+
+            browser = await get_or_create_browser()
+            extractor = LinkedInExtractor(browser.page)
+
+            await ctx.report_progress(
+                progress=0, total=100, message="Starting people search"
+            )
+
+            result = await extractor.search_people(keywords, location)
+
+            await ctx.report_progress(progress=100, total=100, message="Complete")
+
+            return result
+
+        except Exception as e:
+            return handle_tool_error(e, "search_people")

tests/test_tools.py

@@ -40,6 +40,7 @@ def _make_mock_extractor(scrape_result: dict) -> MagicMock:
     mock.scrape_company = AsyncMock(return_value=scrape_result)
     mock.scrape_job = AsyncMock(return_value=scrape_result)
     mock.search_jobs = AsyncMock(return_value=scrape_result)
+    mock.search_people = AsyncMock(return_value=scrape_result)
     mock.extract_page = AsyncMock(return_value="some text")
     return mock
 
@@ -128,6 +129,31 @@ async def test_get_person_profile_error(self, mock_context, monkeypatch):
         result = await tool_fn("test-user", mock_context)
         assert result["error"] == "session_expired"
 
+    async def test_search_people(self, mock_context, patch_tool_deps, monkeypatch):
+        expected = {
+            "url": "https://www.linkedin.com/search/results/people/?keywords=AI+engineer&location=New+York",
+            "sections": {"search_results": "Jane Doe\nAI Engineer at Acme\nNew York"},
+            "pages_visited": [
+                "https://www.linkedin.com/search/results/people/?keywords=AI+engineer&location=New+York"
+            ],
+            "sections_requested": ["search_results"],
+        }
+        mock_extractor = _make_mock_extractor(expected)
+        monkeypatch.setattr(
+            "linkedin_mcp_server.tools.person.LinkedInExtractor",
+            lambda *a, **kw: mock_extractor,
+        )
+
+        from linkedin_mcp_server.tools.person import register_person_tools
+
+        mcp = FastMCP("test")
+        register_person_tools(mcp)
+
+        tool_fn = await get_tool_fn(mcp, "search_people")
+        result = await tool_fn("AI engineer", mock_context, location="New York")
+        assert "search_results" in result["sections"]
+        mock_extractor.search_people.assert_awaited_once_with("AI engineer", "New York")
+
 
 class TestCompanyTools:
     async def test_get_company_profile(