Diogenes Dev & Data Utilities MCP server

• arbitrate_agent_deliverable_escrowFree

  Evaluates a worker agent's submitted task deliverable against agreed contract acceptance criteria to issue a deterministic escrow settlement verdict ('RELEASE_FUNDS_TO_WORKER_AGENT', 'REQUEST_REVISION', or 'REFUND_CLIENT'). Use when settling multi-agent bounties or verifying subcontractor deliverables before releasing MPP/L402 escrow funds; for checking syntactic JSON Schema property types without evaluating semantic contract terms, use enforce_json_schema_types instead. Read-only call (32 KB, 60 RPM): accepts 'deliverable' (with enum defaults), uses '?demo=true' or MPP (30 sats); HTTP 400 if invalid.

• clean_tabular_datasetFree

  Deduplicates repetitive lines or records, normalizes Unicode whitespace, strips HTML/control noise, and canonicalizes tabular text or JSON arrays. Use when cleaning noisy scraped lists, CSV rows, or duplicate log lines before indexing or analysis; for extracting typed JSON fields from free-form prose paragraphs, use extract_structured_json_entities instead. Stateless read-only edge call (max 32 KB, 60 RPM): accepts 'data' ('normalization_mode' defaults to 'exact_match'), supports '?demo=true' or L402 (15 sats), and returns HTTP 400 if invalid.

• compile_xml_agent_promptFree

  Compiles a raw task description into a structured XML system prompt (<role>, <context>, <objective>, <constraints>, <workflow>, <output_format>) engineered to prevent instruction drift. Use when authoring or upgrading a system prompt for an autonomous agent or sub-agent workflow; for mapping a task objective to a concrete sequence of MCP tool calls, use route_mcp_workflow_plan instead. Stateless read-only edge call (max 32 KB, 60 RPM): accepts 'task' ('prompt_style' defaults to 'anthropic_xml_tags'), supports '?demo=true' or L402 (20 sats), and returns HTTP 400 if invalid.

• enforce_json_schema_typesFree

  Validates a raw LLM output object against a target JSON Schema, automatically coercing mismatched scalar types (e.g. string '42' to integer 42), injecting schema defaults, and pruning undeclared hallucinated fields. Use when enforcing schema compliance and type safety on structured LLM outputs before passing them to typed APIs; for healing unparseable raw JSON text with broken quotes or trailing commas, use heal_malformed_json instead. Read-only edge call (32 KB, 60 RPM): accepts 'raw_output' (with enum defaults), uses '?demo=true' or L402 (15 sats); HTTP 400 if invalid.

• extract_structured_json_entitiesFree

  Extracts structured JSON records, named entities, dates, and financial figures from unstructured prose, emails, or HTML/Markdown dumps. Use when converting unstructured natural-language text into a structured JSON array of entities; for validating and coercing an existing JSON payload against a formal JSON Schema, use enforce_json_schema_types instead. Stateless read-only edge call (max 32 KB, 60 RPM): accepts 'text' ('extraction_target' defaults to 'general_entities_and_metrics'), supports '?demo=true' or L402 (25 sats), and returns HTTP 400 if invalid.

• generate_x402_vector_embeddingsFree

  Generates normalized high-dimensional semantic vector embeddings settled via Solana SPL USDC ('x402' protocol headers) for decentralized RAG pipelines. Use when computing text embeddings paid via Solana USDC x402 signatures rather than Bitcoin Lightning; for extracting discrete JSON entities from unstructured text, use extract_structured_json_entities instead. Stateless read-only edge call (max 32 KB, 60 RPM): accepts 'text' ('encoding_format' defaults to 'float_array'), supports '?demo=true' or x402 (10 sats), and returns HTTP 400 if invalid.

• heal_malformed_jsonFree

  Deterministic JSON syntax repair: normalizes quotes, unclosed brackets, and boolean literals into compliant RFC 8259 JSON structure without data deletion. Use when fixing syntax-broken JSON strings that fail JSON.parse(); for coercing field types and verifying properties on already-parseable JSON objects against a target JSON Schema, use enforce_json_schema_types instead. Read-only edge call (32 KB, 60 RPM): accepts 'malformed_json' (with enum defaults), uses '?demo=true' or L402 (15 sats); HTTP 400 if invalid.

• infer_mpp_streaming_sessionFree

  Initializes a Base USDC Machine Payments Protocol (MPP) metered inference session, allocating a streaming token quota and returning a step-by-step execution plan. Use when running session-metered agent planning settled via Base EVM MPP 'Payment-Challenge' headers; for mapping a task goal to L402 MCP tool calls without opening an MPP streaming session, use route_mcp_workflow_plan instead. Stateless read-only edge call (max 32 KB, 60 RPM): accepts 'task' ('token_quota_tier' defaults to 'compact_1024'), supports '?demo=true' or MPP (100 sats), and returns HTTP 400 if invalid.

• route_mcp_workflow_planFree

  Maps a natural-language agent goal to an ordered sequence of Diogenes MCP tool calls with exact endpoint paths, JSON-RPC 2.0 payloads, and cumulative satoshi cost estimates. Use when an autonomous agent needs to plan which MCP tools to chain together to solve a multi-step objective within a satoshi budget; for compiling a static XML system prompt rather than an executable MCP tool call sequence, use compile_xml_agent_prompt instead. Read-only edge call (32 KB, 60 RPM): accepts 'objective' ('budget_preference' defaults to 'lowest_sats_deterministic'), uses '?demo=true' or L402 (20 sats); HTTP 400 if invalid.

• summarize_technical_documentFree

  Condenses long technical specifications, RFCs, research papers, or meeting transcripts into high-density executive bullet points preserving exact figures and decisions. Use when producing a human-readable executive summary of a single provided document; for researching a topic across the live web with Google Search citations, use synthesize_web_intelligence_brief instead. Stateless read-only edge call (max 32 KB, 60 RPM): accepts 'text' ('summary_format' defaults to 'executive_bullets'), supports '?demo=true' or L402 (50 sats), and returns HTTP 400 if invalid.

• synthesize_python_automation_codeFree

  Synthesizes PEP 8 compliant, self-contained Python 3 scripts, data parsers, and CLI utilities complete with type hints, docstrings, and inline assertion tests. Use when generating a standalone Python automation script or parser from a functional specification; for summarizing existing documentation or codebases into executive bullet points, use summarize_technical_document instead. Stateless read-only edge call (max 32 KB, 60 RPM): accepts 'prompt' ('dependency_policy' defaults to 'stdlib_only'), supports '?demo=true' or L402 (75 sats), and returns HTTP 400 if invalid.

• synthesize_safe_regexFree

  Synthesizes linear-time O(n) regular expressions free of catastrophic backtracking (ReDoS) and validates them against positive and negative test strings. Use when generating and verifying a regular expression pattern for input validation or lexical parsing; for repairing broken JSON syntax directly without writing custom regexes, use heal_malformed_json instead. Stateless read-only edge call (max 32 KB, 60 RPM): accepts 'description' ('flavor' defaults to 'ecmascript_js'), supports '?demo=true' or L402 (15 sats), and returns HTTP 400 if invalid.

• synthesize_web_intelligence_briefFree

  Synthesizes a real-time market or technical intelligence brief grounded in live Google Search, returning strict JSON ('executive_summary', 'key_developments', 'sentiment', 'sources'). Use when fetching a structured JSON market/news brief with live web citations and sentiment classification; for summarizing caller-supplied text offline without live web search, use summarize_technical_document instead. Read-only edge call (32 KB, 60 RPM): accepts 'topic' ('focus' defaults to 'technical_and_market_catalysts'), supports '?demo=true' or L402 (75 sats), and returns HTTP 400 if invalid.

• verify_context_compaction_fidelityFree

  Audits a compacted conversation summary against the original full context to detect dropped user constraints, lost file paths, altered numbers, or missing pending tasks. Use when verifying that an LLM context-compaction summary retained all task-critical facts before truncating history; for generating a new executive summary from a raw technical document, use summarize_technical_document instead. Read-only edge call (32 KB, 60 RPM): accepts 'original_context' ('compacted_summary' defaults to 'standard'), supports '?demo=true' or L402 (15 sats), and returns HTTP 400 if invalid.

• –Code scanremote-only server, no package to scann/a
• Live reliabilityremote reachable in 363ms20/20
• Tool poisoning14 tool descriptions checked15/15
• Auth qualityopen endpoint, read-only tools10/15
• Maintenancelast push 0 days ago15/15
• Maintainer identityregistry namespace matches repository owner6/10

Safety score

88/100

higher than 80% of 4,464 AI and agents servers

Tools

14

the typical AI and agents server has 6

Tools that change things

0%

typical: 0%. Fewer write tools means less an agent can break

Uptime

96%

of our recent checks; the typical remote AI and agents server answers 100%

Response time

18 ms

faster than 97% of 2,333 AI and agents servers

GitHub stars

1

more than 50% of 2,697 AI and agents servers

Diogenes Dev & Data Utilities MCP: common questions

Is Diogenes Dev & Data Utilities MCP server safe?

Yes, by our scan: it is graded A (88/100). Read the Diogenes Dev & Data Utilities MCP safety report

How do I install Diogenes Dev & Data Utilities MCP?

It runs remotely at diogenes-micro-gateway.corinth.workers.dev. Add it to Claude Code, Cursor, VS Code or Claude Desktop with the snippets above, or call it through the mcp.market gateway without installing anything.

Does Diogenes Dev & Data Utilities MCP need an API key?

Not as far as the registry entry and our scan can tell: no credentials are declared or required.

Is Diogenes Dev & Data Utilities MCP maintained?

The last commit was 7 days ago (2026-10-26). The latest release is v1.0.0.

Is Diogenes Dev & Data Utilities MCP up?

96% of our last 26 checks got an answer. We check remote servers about four times a day.

What can I use instead of Diogenes Dev & Data Utilities MCP?

Servers from other publishers that do the same job: FireCMS Cloud MCP server, Agent-Native Analytics MCP server and Butterbase AI MCP server.

How does Diogenes Dev & Data Utilities MCP compare with other AI and agents MCP servers?

safety score 88/100 (higher than 80% of 4,464 AI and agents servers); tools 14 (the typical AI and agents server has 6); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.