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Glama

Veezee: LinkedIn people & company data for agents

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Server Details

LinkedIn data for AI agents: structured profiles, people search, companies, and posts over MCP or REST. 500 free credits, no card.

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.

MCP client
Glama
MCP server

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.

100% free. Your data is private.
Tool DescriptionsA

Average 4.8/5 across 7 of 7 tools scored.

Server CoherenceA
Disambiguation5/5

Each tool targets a distinct LinkedIn data type or action: company, profile, posts, URL resolve, account usage, account creation, and people search. No two tools overlap in purpose, so an agent can clearly distinguish them.

Naming Consistency5/5

Tool names follow a consistent verb_noun pattern using snake_case (get_*, provision, resolve_url, search_people). The get_ prefix is uniformly used for data retrieval, and other verbs are clear and predictable.

Tool Count5/5

With 7 tools, the server is well-scoped for its purpose of providing LinkedIn people and company data. Each tool serves a distinct function without unnecessary duplication, and the count feels right for a focused API.

Completeness4/5

The tool set covers core operations: fetching company, profile, posts, searching people, account management, and URL resolution. However, search for companies by name lacks a direct tool (use people search with company filter) and there is no post search or single post retrieval, but these are acceptable for a v1.

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