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    <title>PyPI recent updates for neruva-mcp</title>
    <link>https://pypi.org/project/neruva-mcp/</link>
    <description>Recent updates to the Python Package Index for neruva-mcp</description>
    <language>en</language>    <item>
      <title>0.21.1</title>
      <link>https://pypi.org/project/neruva-mcp/0.21.1/</link>
      <description>MCP server for Neruva agent memory + reasoning substrate. v0.21 adds code_kg_callees/callers/class_of/module_of/imports for sub-ms structural code queries on KGs built locally via neruva-record-code-index. Plus Records, 5-engine KG, federated agent_remember/recall/context, Pearl do-operator, HD analogy, CBR, ToM, counterfactual rollouts, schema lifting, EFE, continual K-gram, rule induction, replay, .neruva V3. MCP drop-in for Claude Code, Cursor, Codex, Gemini CLI.</description>
<author>info@neruva.io</author>      <pubDate>Thu, 21 May 2026 23:48:58 GMT</pubDate>
    </item>    <item>
      <title>0.21.0</title>
      <link>https://pypi.org/project/neruva-mcp/0.21.0/</link>
      <description>MCP server for Neruva agent memory + reasoning substrate. v0.21 adds code_kg_callees/callers/class_of/module_of/imports for sub-ms structural code queries on KGs built locally via neruva-record-code-index. Removes agent_postmortem_prompt (transport stall). Plus Records, 5-engine KG, federated agent_remember/recall/context, Pearl do-operator, HD analogy, CBR, ToM, counterfactual rollouts, schema lifting, EFE, continual K-gram, rule induction, replay, .neruva V3. MCP drop-in for Claude Code, Cursor, Codex.</description>
<author>info@neruva.io</author>      <pubDate>Thu, 21 May 2026 23:37:13 GMT</pubDate>
    </item>    <item>
      <title>0.20.0</title>
      <link>https://pypi.org/project/neruva-mcp/0.20.0/</link>
      <description>MCP server for Neruva agent memory + reasoning substrate. v0.20 adds code_kg_callees/callers/class_of/module_of/imports for sub-ms structural code queries on KGs built locally via neruva-record-code-index. Plus Records, 5-engine KG, federated agent_remember/recall/context, Pearl do-operator, HD analogy, CBR, ToM, counterfactual rollouts, schema lifting, EFE, continual K-gram, rule induction, replay, .neruva V3. MCP drop-in for Claude Code, Cursor, Codex.</description>
<author>info@neruva.io</author>      <pubDate>Thu, 21 May 2026 23:20:02 GMT</pubDate>
    </item>    <item>
      <title>0.19.0</title>
      <link>https://pypi.org/project/neruva-mcp/0.19.0/</link>
      <description>MCP server for Neruva agent memory + reasoning substrate. Records, 5-engine KG (OPB / quorum / multishard / feature-bundle / Hadamard), federated agent_remember/recall/context, Pearl do-operator, HD analogy, CBR, concept blend. Cognitive primitives: depth-unlimited theory of mind, counterfactual rollouts, schema lifting, EFE planning, continual learning, hierarchical chunking, rule induction. Snapshot/restore replay. .neruva container. Drop into Claude Code / Cursor / Codex / Gemini CLI. Sub-100ms p95.</description>
<author>info@neruva.io</author>      <pubDate>Thu, 21 May 2026 12:41:10 GMT</pubDate>
    </item>    <item>
      <title>0.18.5</title>
      <link>https://pypi.org/project/neruva-mcp/0.18.5/</link>
      <description>MCP server for Neruva agent memory + reasoning substrate. Records, 5-engine KG (OPB / quorum / multishard / feature-bundle / Hadamard), federated agent_remember/recall/context, Pearl do-operator, HD analogy, CBR, concept blend. Cognitive primitives: depth-unlimited theory of mind, counterfactual rollouts, schema lifting, EFE planning, continual learning, hierarchical chunking, rule induction. Snapshot/restore replay. .neruva container. Drop into Claude Code / Cursor / Codex / Gemini CLI. Sub-100ms p95.</description>
<author>info@neruva.io</author>      <pubDate>Tue, 19 May 2026 21:10:40 GMT</pubDate>
    </item>    <item>
      <title>0.18.4</title>
      <link>https://pypi.org/project/neruva-mcp/0.18.4/</link>
      <description>MCP server for Neruva agent memory + reasoning substrate. Records, 5-engine KG (OPB / quorum / multishard / feature-bundle / Hadamard), federated agent_remember/recall/context, Pearl do-operator, HD analogy, CBR, concept blend. Cognitive primitives: depth-unlimited theory of mind, counterfactual rollouts, schema lifting, EFE planning, continual learning, hierarchical chunking, rule induction. Snapshot/restore replay. .neruva container. Drop into Claude Code / Cursor / Codex / Gemini CLI. Sub-100ms p95.</description>
<author>info@neruva.io</author>      <pubDate>Tue, 19 May 2026 03:33:02 GMT</pubDate>
    </item>    <item>
      <title>0.18.3</title>
      <link>https://pypi.org/project/neruva-mcp/0.18.3/</link>
      <description>MCP server for Neruva agent memory: typed Records, 5-engine knowledge graph, managed/BYO-LLM extraction, federated agent_remember/recall/context with question-type dispatch, Pearl&#39;s do-operator, HD analogy, concept blending, CBR, snapshot/restore for provable replay, quorum anomaly detection, fact invalidation, portable .neruva container. Drop-in for any MCP host (Claude Code, Cursor, Codex, Gemini CLI). LangChain / LangGraph / CrewAI adapters. Sub-100ms p95.</description>
<author>info@neruva.io</author>      <pubDate>Tue, 19 May 2026 02:16:05 GMT</pubDate>
    </item>    <item>
      <title>0.18.2</title>
      <link>https://pypi.org/project/neruva-mcp/0.18.2/</link>
      <description>MCP server for Neruva agent memory: typed Records, 5-engine knowledge graph, managed/BYO-LLM extraction, federated agent_remember/recall/context with question-type dispatch, Pearl&#39;s do-operator, HD analogy, concept blending, CBR, snapshot/restore for provable replay, quorum anomaly detection, fact invalidation, portable .neruva container. Drop-in for any MCP host (Claude Code, Cursor, Codex, Gemini CLI). LangChain / LangGraph / CrewAI adapters. Sub-100ms p95.</description>
<author>info@neruva.io</author>      <pubDate>Tue, 19 May 2026 01:40:49 GMT</pubDate>
    </item>    <item>
      <title>0.18.1</title>
      <link>https://pypi.org/project/neruva-mcp/0.18.1/</link>
      <description>MCP server for Neruva agent memory: typed Records, 5-engine knowledge graph, managed/BYO-LLM extraction, federated agent_remember/recall/context with question-type dispatch, Pearl&#39;s do-operator, HD analogy, concept blending, CBR, snapshot/restore for provable replay, quorum anomaly detection, fact invalidation, portable .neruva container. Drop-in for any MCP host (Claude Code, Cursor, Codex, Gemini CLI). LangChain / LangGraph / CrewAI adapters. Sub-100ms p95.</description>
<author>info@neruva.io</author>      <pubDate>Tue, 19 May 2026 00:55:25 GMT</pubDate>
    </item>    <item>
      <title>0.18.0</title>
      <link>https://pypi.org/project/neruva-mcp/0.18.0/</link>
      <description>MCP server for Neruva agent memory: typed Records, 5-engine knowledge graph, managed/BYO-LLM extraction, federated agent_remember/recall/context with question-type dispatch, Pearl&#39;s do-operator, HD analogy, concept blending, CBR, snapshot/restore for provable replay, quorum anomaly detection, fact invalidation, portable .neruva container. Drop-in for any MCP host (Claude Code, Cursor, Codex, Gemini CLI). LangChain / LangGraph / CrewAI adapters. Sub-100ms p95.</description>
<author>info@neruva.io</author>      <pubDate>Mon, 18 May 2026 23:44:03 GMT</pubDate>
    </item>    <item>
      <title>0.17.0</title>
      <link>https://pypi.org/project/neruva-mcp/0.17.0/</link>
      <description>MCP server for Neruva agent memory: typed Records, 5-engine knowledge graph, managed/BYO-LLM extraction, federated agent_remember/recall/context with question-type dispatch, Pearl&#39;s do-operator, HD analogy, concept blending, CBR, snapshot/restore for provable replay, quorum anomaly detection, fact invalidation, portable .neruva container. Drop-in for any MCP host (Claude Code, Cursor, Codex, Gemini CLI). LangChain / LangGraph / CrewAI adapters. Sub-100ms p95.</description>
<author>info@neruva.io</author>      <pubDate>Mon, 18 May 2026 22:56:31 GMT</pubDate>
    </item>    <item>
      <title>0.16.3</title>
      <link>https://pypi.org/project/neruva-mcp/0.16.3/</link>
      <description>MCP server for Neruva agent memory: typed Records, 5-engine knowledge graph, managed/BYO-LLM extraction, federated agent_remember/recall/context with question-type dispatch, Pearl&#39;s do-operator, HD analogy, concept blending, CBR, snapshot/restore for provable replay, quorum anomaly detection, fact invalidation, portable .neruva container. Drop-in for any MCP host (Claude Code, Cursor, Codex, Gemini CLI). LangChain / LangGraph / CrewAI adapters. Sub-100ms p95.</description>
<author>info@neruva.io</author>      <pubDate>Mon, 18 May 2026 18:11:09 GMT</pubDate>
    </item>    <item>
      <title>0.16.2</title>
      <link>https://pypi.org/project/neruva-mcp/0.16.2/</link>
      <description>MCP server for Neruva agent memory: typed Records, 5-engine knowledge graph, managed/BYO-LLM extraction, federated agent_remember/recall/context with question-type dispatch, Pearl&#39;s do-operator, HD analogy, concept blending, CBR, snapshot/restore for provable replay, quorum anomaly detection, fact invalidation, portable .neruva container. Drop-in for any MCP host (Claude Code, Cursor, Codex, Gemini CLI). LangChain / LangGraph / CrewAI adapters. Sub-100ms p95.</description>
<author>info@neruva.io</author>      <pubDate>Sun, 17 May 2026 18:07:22 GMT</pubDate>
    </item>    <item>
      <title>0.16.1</title>
      <link>https://pypi.org/project/neruva-mcp/0.16.1/</link>
      <description>MCP server for Neruva agent memory: typed Records, 5-engine knowledge graph, managed/BYO-LLM extraction, federated agent_remember/recall/context with question-type dispatch, Pearl&#39;s do-operator, HD analogy, concept blending, CBR, snapshot/restore for provable replay, quorum anomaly detection, fact invalidation, portable .neruva container. Drop-in for any MCP host (Claude Code, Cursor, Codex, Gemini CLI). LangChain / LangGraph / CrewAI adapters. Sub-100ms p95.</description>
<author>info@neruva.io</author>      <pubDate>Sat, 16 May 2026 19:15:24 GMT</pubDate>
    </item>    <item>
      <title>0.16.0</title>
      <link>https://pypi.org/project/neruva-mcp/0.16.0/</link>
      <description>Model Context Protocol server for Neruva — typed agentic memory (Records: decisions, mistakes, llm_turns, tool_calls), knowledge graph with 4 engines (Hadamard / OPB / multi-shard / quorum / feature-bundle) + raw-text ingest + N-hop matrix-power derive + customizable context blocks, Pearl&#39;s do-operator, HD analogy, plus self-introspection (wallet, op stats, op log, keys). Drop-in for any MCP host.</description>
<author>info@neruva.io</author>      <pubDate>Sat, 16 May 2026 19:08:46 GMT</pubDate>
    </item>    <item>
      <title>0.15.0</title>
      <link>https://pypi.org/project/neruva-mcp/0.15.0/</link>
      <description>Model Context Protocol server for Neruva — typed agentic memory (Records: decisions, mistakes, llm_turns, tool_calls), knowledge graph with 4 engines (Hadamard / OPB / multi-shard / quorum / feature-bundle) + raw-text ingest + N-hop matrix-power derive + customizable context blocks, Pearl&#39;s do-operator, HD analogy, plus self-introspection (wallet, op stats, op log, keys). Drop-in for any MCP host.</description>
<author>info@neruva.io</author>      <pubDate>Sat, 16 May 2026 18:42:45 GMT</pubDate>
    </item>    <item>
      <title>0.14.0</title>
      <link>https://pypi.org/project/neruva-mcp/0.14.0/</link>
      <description>Model Context Protocol server for Neruva — typed agentic memory (Records: decisions, mistakes, llm_turns, tool_calls), knowledge graph with 4 engines (Hadamard / OPB / multi-shard / quorum / feature-bundle) + raw-text ingest + N-hop matrix-power derive + customizable context blocks, Pearl&#39;s do-operator, HD analogy, plus self-introspection (wallet, op stats, op log, keys). Drop-in for any MCP host.</description>
<author>info@neruva.io</author>      <pubDate>Sat, 16 May 2026 17:17:38 GMT</pubDate>
    </item>    <item>
      <title>0.13.1</title>
      <link>https://pypi.org/project/neruva-mcp/0.13.1/</link>
      <description>Model Context Protocol server for Neruva — typed agentic memory (Records: decisions, mistakes, llm_turns, tool_calls), knowledge graph with 4 engines (Hadamard / OPB / multi-shard / quorum / feature-bundle) + raw-text ingest + N-hop matrix-power derive + customizable context blocks, Pearl&#39;s do-operator, HD analogy, plus self-introspection (wallet, op stats, op log, keys). Drop-in for any MCP host.</description>
<author>info@neruva.io</author>      <pubDate>Sat, 16 May 2026 16:36:29 GMT</pubDate>
    </item>    <item>
      <title>0.13.0</title>
      <link>https://pypi.org/project/neruva-mcp/0.13.0/</link>
      <description>Model Context Protocol server for Neruva — typed agentic memory (Records: decisions, mistakes, llm_turns, tool_calls), knowledge graph with 4 engines (Hadamard / OPB / multi-shard / quorum / feature-bundle) + raw-text ingest + N-hop matrix-power derive + customizable context blocks, Pearl&#39;s do-operator, HD analogy, plus self-introspection (wallet, op stats, op log, keys). Drop-in for any MCP host.</description>
<author>info@neruva.io</author>      <pubDate>Sat, 16 May 2026 15:53:40 GMT</pubDate>
    </item>    <item>
      <title>0.12.0</title>
      <link>https://pypi.org/project/neruva-mcp/0.12.0/</link>
      <description>Model Context Protocol server for Neruva — typed agentic memory (Records: decisions, mistakes, llm_turns, tool_calls), knowledge graph with 4 engines (Hadamard / OPB / multi-shard / quorum / feature-bundle) + raw-text ingest + N-hop matrix-power derive + customizable context blocks, Pearl&#39;s do-operator, HD analogy, plus self-introspection (wallet, op stats, op log, keys). Drop-in for any MCP host.</description>
<author>info@neruva.io</author>      <pubDate>Sat, 16 May 2026 15:30:18 GMT</pubDate>
    </item>    <item>
      <title>0.10.0</title>
      <link>https://pypi.org/project/neruva-mcp/0.10.0/</link>
      <description>Model Context Protocol server for Neruva — typed agentic memory (Records: decisions, mistakes, llm_turns, tool_calls), knowledge graph with 4 engines (Hadamard / OPB / multi-shard / quorum / feature-bundle) + raw-text ingest + N-hop matrix-power derive + customizable context blocks, Pearl&#39;s do-operator, HD analogy, plus self-introspection (wallet, op stats, op log, keys). Drop-in for any MCP host.</description>
<author>info@neruva.io</author>      <pubDate>Sat, 16 May 2026 15:13:44 GMT</pubDate>
    </item>    <item>
      <title>0.9.0</title>
      <link>https://pypi.org/project/neruva-mcp/0.9.0/</link>
      <description>Model Context Protocol server for Neruva — typed agentic memory (Records: decisions, mistakes, llm_turns, tool_calls), knowledge graph with 4 engines (Hadamard / OPB / multi-shard / quorum / feature-bundle) + raw-text ingest + N-hop matrix-power derive + customizable context blocks, Pearl&#39;s do-operator, HD analogy, plus self-introspection (wallet, op stats, op log, keys). Drop-in for any MCP host.</description>
<author>info@neruva.io</author>      <pubDate>Sat, 16 May 2026 13:51:29 GMT</pubDate>
    </item>    <item>
      <title>0.7.1</title>
      <link>https://pypi.org/project/neruva-mcp/0.7.1/</link>
      <description>Model Context Protocol server for Neruva — typed agentic memory (Records: decisions, mistakes, llm_turns, tool_calls), knowledge graph, Pearl&#39;s do-operator, HD analogy, plus self-introspection (wallet, op stats, op log, keys). Drop-in for any MCP host.</description>
<author>info@neruva.io</author>      <pubDate>Fri, 15 May 2026 01:25:57 GMT</pubDate>
    </item>    <item>
      <title>0.7.0</title>
      <link>https://pypi.org/project/neruva-mcp/0.7.0/</link>
      <description>Model Context Protocol server for Neruva — typed Records substrate (decisions, mistakes, llm_turns, tool_calls), KG, causal do-operator, analogy, and a Pinecone-compatible memory layer. Drop-in for any MCP host.</description>
<author>info@neruva.io</author>      <pubDate>Fri, 15 May 2026 00:35:46 GMT</pubDate>
    </item>    <item>
      <title>0.6.1</title>
      <link>https://pypi.org/project/neruva-mcp/0.6.1/</link>
      <description>Model Context Protocol server for Neruva — typed Records substrate (decisions, mistakes, llm_turns, tool_calls), KG, causal do-operator, analogy, and a Pinecone-compatible memory layer. Drop-in for any MCP host.</description>
<author>info@neruva.io</author>      <pubDate>Thu, 14 May 2026 13:11:44 GMT</pubDate>
    </item>    <item>
      <title>0.6.0</title>
      <link>https://pypi.org/project/neruva-mcp/0.6.0/</link>
      <description>Model Context Protocol server for Neruva — typed Records substrate (decisions, mistakes, llm_turns, tool_calls), KG, causal do-operator, analogy, and a Pinecone-compatible memory layer. Drop-in for any MCP host.</description>
<author>info@neruva.io</author>      <pubDate>Thu, 14 May 2026 12:55:19 GMT</pubDate>
    </item>    <item>
      <title>0.5.0</title>
      <link>https://pypi.org/project/neruva-mcp/0.5.0/</link>
      <description>Model Context Protocol server for Neruva — typed Records substrate (decisions, mistakes, llm_turns, tool_calls), KG, causal do-operator, analogy, and a Pinecone-compatible memory layer. Drop-in for any MCP host.</description>
<author>info@neruva.io</author>      <pubDate>Thu, 14 May 2026 12:11:19 GMT</pubDate>
    </item>    <item>
      <title>0.4.1</title>
      <link>https://pypi.org/project/neruva-mcp/0.4.1/</link>
      <description>Model Context Protocol server for Neruva — text-embeddable Pinecone-compatible vector memory + HD-native substrate (knowledge graphs, analogy, causal do-operator). Drop-in for any MCP host.</description>
<author>info@neruva.io</author>      <pubDate>Thu, 14 May 2026 02:08:23 GMT</pubDate>
    </item>    <item>
      <title>0.4.0</title>
      <link>https://pypi.org/project/neruva-mcp/0.4.0/</link>
      <description>Model Context Protocol server for Neruva — text-embeddable Pinecone-compatible vector memory + HD-native substrate (knowledge graphs, analogy, causal do-operator). Drop-in for any MCP host.</description>
<author>info@neruva.io</author>      <pubDate>Thu, 14 May 2026 02:01:06 GMT</pubDate>
    </item>    <item>
      <title>0.3.4</title>
      <link>https://pypi.org/project/neruva-mcp/0.3.4/</link>
      <description>Model Context Protocol server for Neruva — text-embeddable Pinecone-compatible vector memory + HD-native substrate (knowledge graphs, analogy, causal do-operator). Drop-in for any MCP host.</description>
<author>info@neruva.io</author>      <pubDate>Thu, 14 May 2026 00:41:37 GMT</pubDate>
    </item>    <item>
      <title>0.3.3</title>
      <link>https://pypi.org/project/neruva-mcp/0.3.3/</link>
      <description>Model Context Protocol server for Neruva — text-embeddable Pinecone-compatible vector memory + HD-native substrate (knowledge graphs, analogy, causal do-operator). Drop-in for any MCP host.</description>
<author>info@neruva.io</author>      <pubDate>Thu, 14 May 2026 00:26:58 GMT</pubDate>
    </item>    <item>
      <title>0.3.2</title>
      <link>https://pypi.org/project/neruva-mcp/0.3.2/</link>
      <description>Model Context Protocol server for Neruva — text-embeddable Pinecone-compatible vector memory + HD-native substrate (knowledge graphs, analogy, causal do-operator). Drop-in for any MCP host.</description>
<author>info@neruva.io</author>      <pubDate>Thu, 14 May 2026 00:00:42 GMT</pubDate>
    </item>    <item>
      <title>0.3.0</title>
      <link>https://pypi.org/project/neruva-mcp/0.3.0/</link>
      <description>Model Context Protocol server for Neruva — vector memory + HD-native substrate (KGs, analogy, causal do-operator, EFE planning).</description>
<author>info@neruva.io</author>      <pubDate>Wed, 13 May 2026 23:29:44 GMT</pubDate>
    </item>    <item>
      <title>0.2.0</title>
      <link>https://pypi.org/project/neruva-mcp/0.2.0/</link>
      <description>Model Context Protocol server for Neruva — vector memory + HD-native substrate (KGs, analogy, causal do-operator, EFE planning).</description>
<author>info@neruva.io</author>      <pubDate>Wed, 13 May 2026 23:00:51 GMT</pubDate>
    </item>    <item>
      <title>0.1.2</title>
      <link>https://pypi.org/project/neruva-mcp/0.1.2/</link>
      <description>Model Context Protocol server for Neruva — vector memory + HD-native substrate (KGs, analogy, causal do-operator, EFE planning).</description>
<author>info@neruva.io</author>      <pubDate>Wed, 13 May 2026 22:32:08 GMT</pubDate>
    </item>    <item>
      <title>0.1.1</title>
      <link>https://pypi.org/project/neruva-mcp/0.1.1/</link>
      <description>Model Context Protocol server for Neruva — vector memory + HD-native substrate (KGs, analogy, causal do-operator, EFE planning).</description>
<author>info@neruva.io</author>      <pubDate>Wed, 13 May 2026 22:01:27 GMT</pubDate>
    </item>    <item>
      <title>0.1.0</title>
      <link>https://pypi.org/project/neruva-mcp/0.1.0/</link>
      <description>Model Context Protocol server for Neruva — vector memory + HD-native substrate (KGs, analogy, causal do-operator, EFE planning).</description>
<author>info@neruva.io</author>      <pubDate>Wed, 13 May 2026 13:22:37 GMT</pubDate>
    </item>  </channel>
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