These include more than 20 Model Context Protocol (MCP) connectors that link Claude to legal industry software, and 12 plugins for specific legal work and practice areas, the company said in a Tuesday (May 12) blog post.
“Earlier this year we released our first legal plugin, and in the months since, legal professionals have become the most engaged Claude Cowork users of any knowledge-work function,” Anthropic said in the post. “We’re now building on that with a much larger set of tools.”
The new MCP connectors enable Claude to connect with commonly used legal industry systems for contract lifecycle and drafting; deal rooms and transaction documents; document management; expert networks and skills; eDiscovery and review; fiduciary-grade workflows; legal research and case law; legal AI assistants; and public service.
The 12 practice-area plugins are each built around a specific legal role and can be tailored to each team. Each agent template can be installed in Cowork or Claude Code, and teams can customize the skills.
“These updates build on Claude Opus 4.7, our most capable publicly available model for legal reasoning and long-document work,” Anthropic said in the post.
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It was reported that Anthropic’s launch of a Cowork legal plugin in February wiped $285 billion from tech stocks within 24 hours due to concerns that this product would threaten existing enterprise software.
PYMNTS reported in October that AI was making inroads into the legal industry, with AI systems becoming embedded infrastructure in law firms and in-house operations.
As investors took notice, funding to legal technology startups surpassed $2.4 billion in the first nine months of 2025.
The surge in funding reflected confidence that automation can relieve the legal sector’s document-heavy workloads and unlock new operating leverage for firms, according to the report.
When Anthropic announced in February that it closed a Series G funding round in which it raised $30 billion and was valued at $380 billion, the company attributed investors’ interest in part to its strength in enterprise AI and coding. The company said its run-rate revenue had grown to $14 billion at that time, driven by demand from enterprises and developers.
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