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#MCP and tools

1091 stories · 135 in 7 days · 462 in 30 days · Topic watch →
agents 400Claude 95coding assistants 90Claude Code 73Anthropic 54LangChain 52prompt engineering 46ChatGPT 42
Oct 23
ProductsBuildersMulti-sourceSelected05:36
Claude API Now Available Through Google Cloud Accounts

Billing and contracting through Google Cloud lowers the barrier for enterprises already committed to Google's ecosystem, removing the need for a separate Anthropic account. Teams building agents or running code-execution workflows can consolidate vendor relationships and procurement into one cloud bill. It also puts Claude in more direct competition with Google's own Gemini models inside Google Cloud's own marketplace.

#Claude#Google Cloud#Anthropic#MCP and tools
Event
claudedevs@claudedevsSource
Oct 22
ProductsBuildersSelected09:24
Hermes Agent adds official Meshy plugin for 3D generation

Agent frameworks are starting to absorb 3D content creation as a native skill, not just text or image tasks. Developers building games in Godot or prototyping printable models can now delegate asset generation to an agent without leaving their chat workflow. Compared with calling Meshy's web app directly, the plugin adds inline rendering, animation previews and persistent prompt history.

#Hermes Agent#MeshyAI#MCP and tools#3D generation
Official accountNous Research@NousResearchSource
How-toBuildersOfficial05:47
Chinese content用 Strands Agents 构建自适应智能体框架：本地 SLM 处理简单任务，复杂请求走 Amazon Bedrock

AWS 教程教你怎么用 Strands Agents 搭一套混合架构：简单活儿让 Ollama 本地小模型干，难活儿丢给 Bedrock 云端模型，还带 IoT 监控实例。

#Strands Agents#Amazon Bedrock#Ollama#agents
Event
Primary sourceAWS Machine Learning Blog@Nitin EusebiusSource
How-toBuildersSelected02:26
Kena's web index cuts agent search output tokens by 50%

Token-level scoring over its own index means agents fetch only the passages that matter, which lowers API costs for teams running frequent web searches. Builders wiring up agents through MCP or API can swap in KeenableAI as a search backend and immediately halve the tokens their pipeline pays for. Compared with generic search APIs that return whole snippets, this targets long-document retrieval where most waste happens.

#Kena#MCP and tools#agents#RAG
Ate-a-Pi@svpinoSource
Oct 21
ProductsBuildersOfficialSelected02:30
OpenAI adds 12-hour prompt caching to its API

Longer cache windows change the economics of always-on agents, since hourly or daily recurring calls can now hit cached-input pricing instead of full-price tokens. Teams building background assistants or scheduled workflows on the OpenAI API should re-check their token spend, as cost drops apply to any workload with repeated shared context.

#OpenAI#prompt caching#MCP and tools
Event
Primary source@OpenAIDevs@OpenAIDevsSource
How-toBuildersSelected00:56
Zed benchmarks 25 approaches to MCP tool search

A classical retrieval baseline beating neural methods changes how developers should think about MCP tool discovery — embeddings and LLM routing may be unnecessary complexity for most setups. Builders implementing agent tool selection can adopt weighted BM25 locally without API costs or latency. The benchmark size of 536 tools offers a concrete reference point for comparing their own retrieval setups.

#MCP and tools#BM25#Zed#information retrieval
Zed@zeddotdevSource
How-toBuildersOfficialSelected00:36
AWS Agent Registry Adds Runtime Tool Discovery for Agents

Runtime discovery changes agent architecture: registries become the integration layer, and new tools can be added without redeploying the orchestrator. Developers building multi-agent systems on AWS can adopt this pattern to keep large tool catalogs maintainable, using MCP and A2A standards already gaining traction across the ecosystem.

#AWS Agent Registry#MCP and tools#A2A#agents
Primary sourceAWS Machine Learning Blog@Vibhu PareekSource
How-toBuildersOfficialSelected00:13
AWS publishes X.509 PKI reference architecture for agent identity

The architecture shows how x509 certificate chains can bind a specific agent instance to delegated user permissions, closing the spoofing gap that plagues token-only agent stacks. Engineers building multi-agent or MCP deployments on AWS can reuse the pattern with EJBCA and OCSP directly. It also gives security teams a concrete baseline to compare against their current agent authentication design.

#AWS#MCP and tools#agents#AI safety
Primary sourceAWS Machine Learning Blog@Deepakkumar SharmaSource
Oct 20
How-toBuildersOfficialSelected23:49
Strategy Mosaic and Amazon Bedrock AgentCore build semantic layers for agents

The non-obvious part is that governance travels through the MCP server: an agent querying a semantic layer still respects per-user row and column security, which removes the usual fear of agents leaking data they can technically reach. Data engineers and agent builders on AWS can follow the walkthrough to combine Redshift, Aurora, Strands and AgentCore into one governed setup. It also serves as a concrete reference implementation of MCP in an enterprise BI context.

#Amazon Bedrock AgentCore#Strategy Mosaic#MCP and tools#agents
Primary sourceAWS Machine Learning Blog@Zhili ChengSource
How-toBuildersOfficialSelected23:48
AtScale MCP Server Connects Bedrock AgentCore Agents to Governed Data

Governance for agentic analytics is often bolted onto prompts, which is fragile and unauditable; this shows enforcement moving down into the data layer itself. Data engineers and platform teams building agents on AWS can follow the walkthrough to expose Redshift models safely through MCP. The pattern applies anywhere enterprises need row-level security for AI agents, with AtScale as the named alternative to hand-rolled semantic layers.

#Amazon Bedrock AgentCore#AtScale#MCP and tools#agents
Primary sourceAWS Machine Learning Blog@Frank LapolitoSource